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Best Paper Awards

Congratulations to the recipients of the ICC 2024 Best Paper Awards. These papers were selected as the result of a rigorous process that considered the 939 symposium papers that were accepted from the 2,364 submissions. The co-chairs of each symposium nominated a set of top papers for the award, and these nominations were reviewed by a committee of 19 respected scholars. The committee considered each nominated paper, its reviewer comments, and a nomination statement by the symposium co-chairs. As a result of the process, a total of 15 papers were selected by the committee for the award – one paper for each of the regular symposia and three papers for the Selected Areas in Communications Symposium. Below, you will find the members of the Best Paper Awards Selection Committee along with the list of the recipients of the award. 

ICC 2024 BEST PAPER AWARDS COMMITTEE

CHAIR Wenjing Lou, Virginia Tech, USA

APPOINTED MEMBERS

Lin Cai, University of Victoria, Canada Yingying Chen, Rutgers University, USA Kaushik Chowdhury, Northeastern University, USA Roberto Di Pietro, King Abdullah University of Science and Technology (KAUST), Saudi Arabia Falko Dressler, TU Berlin, Germany Yusheng Ji, National Institute of Informatics, Japan Admela Jukan, Technische Universität Carolo-Wilhelmina zu Braunschweig (Brunswick), Germany Loukas Lazos, University of Arizona, USA Satyajayant Misra, New Mexico State University, USA Alex Sprintson, Texas A&M University, USA Mehmet Vuran, University of Nebraska-Lincoln, USA Tilman Wolf, University of Massachusetts Amherst, USA Aylin Yener, Ohio State University, USA Yanchao Zhang, Arizona State University, USA Lizhong Zheng, Massachusetts Institute of Technology, USA

EX-OFFICIO MEMBERS

Matthew Valenti, West Virginia University, USA Chonggang Wang, Interdigital, USA Wenye Wang, North Carolina State University, USA

ICC 2024 BEST PAPER AWARDS RECIPIENTS

IOT & SENSOR NETWORKS SYMPOSIUM PEOPLEx: PEdestrian Opportunistic Positioning LEveraging IMU, UWB, BLE and WiFi Pierre-Yves Lajoie, Bobak H Hamed Baghi, Sachini Herath, Francois Hogan, Xue Liu, and Gregory Dudek

COGNITIVE RADIO & AI-ENABLED NETWORKS Channel Prediction-Enhanced Intelligent Resource Allocation for Dynamic Spectrum-Sharing Networks Lu Yuan, Fuhui Zhou, Qihui Wu, and Derrick Wing Kwan Ng

COMMUNICATION & INFORMATION SYSTEM SECURITY Secure, Available, Verifiable, and Efficient Range Query Processing on Outsourced Datasets Meng Li, Jianbo Gao, Zijian Zhang, Mauro Conti, and Mamoun Alazab

COMMUNICATION QOS, RELIABILITY, & MODELING AI-enabled Traffic Flow-Prediction and Function-Configuration for 5G Networks: An Integrated Design of High Reliability and Low Cost Qianqian Pan and Akihiro Nakao

COMMUNICATION SOFTWARE & MULTIMEDIA Adaptive 360-Degree Video Streaming with Multi-window and Stochastic Viewport Prediction Weichao Feng, Yu Dai, and Shuoyao Wang

COMMUNICATION THEORY On the Information Leakage Performance of Secure Finite Blocklength Transmissions over Rayleigh Fading Channels Milad Tatar Mamaghani, Xiangyun Zhou, Nan Yang, Lee Swindlehurst, and H. Vincent Poor

GREEN COMMUNICATION SYSTEMS & NETWORKS Power-Managed Data Centers for Sustainable Computing Emi Zeger, Nicholas Bambos, and Mert Pilanci

MOBILE & WIRELESS NETWORKS Digital versus Analog Transmissions for Federated Learning over Wireless Networks Jiacheng Yao, Wei Xu, Zhaohui Yang, Xiaohu You, Mehdi Bennis, and H. Vincent Poor

NEXT-GENERATION NETWORKING & INTERNET A Traffic-aware Trust Model Based on Edge Computing for Underwater Wireless Sensor Networks Rongxin Zhu, Azzedine Boukerche, Pengcheng Li, and Qiuling Yang

OPTICAL NETWORKS & SYSTEMS Secret Key Generation in Multi-Mode Fiber Channels: Channel Measurements and Achievable Rates Pin-Hsun Lin, Paul Nowitzki, Eduard A Jorswieck, Dennis Pohlea, and Jürgen Czarske

SIGNAL PROCESSING FOR COMMUNICATIONS Joint Transceiver Design for MIMO Radar With One-Bit DACs and ADCs Qi Lin, Hong Shen, Wei Xu, Chunming Zhao, and Xiaohu You

WIRELESS COMMUNICATIONS Learning-based Deterministic Scheduling for TSN and 5G Integrated Networks Ruibin Guo, Dong Yang, Weiting Zhang, Qingyu Cai, Hongke Zhang, and Xuemin Sherman Shen

SAC - Machine Learning for Communications and Networking X-CBA: Explainability Aided CatBoosted Anomal-E for Intrusion Detection System Kıymet Kaya, Elif Ak, Sumeyye Bas, Berk Canberk, and Şule Gündüz Öğüdücü

SAC – Molecular, Biological, and Multi-Scale Communications

Ultrasound-enabled SIMO Channel for Targeted Brain Cancer Chemotherapy Mohamad Zoofaghari, Martin Damrath, Mladen Veletić, and Ilangko Balasingham

SAC – Backhaul/Fronthaul Networking and Communications

Free-Space Optical Communication System with Wide-Steering Beam for Terrestrial Access Networks Yohei Hasegawa, Atsushi Kamoi, Masaki Aizono, and Takeshi Kato

Diamond Patrons

Silver Patrons

Bronze Patrons

Conference Awards Committee IEEE VR 2024

Conference awards chairs.

• Frank Steinicke ‒ Universität Hamburg, Germany
• Shi-Min Hu ‒ Tsinghua University, China
• Kiyoshi Kiyokawa ‒ Nara Institute of Science and Technology, Japan
• Luciana Nedel ‒ Federal University of Rio Grande do Sul, Brazil
• Missie Smith ‒ Meta Reality Labs, USA

Best Papers & Honorable Mentions

The IEEE VR Best Paper Awards honor exceptional papers published and presented at the IEEE VR conference. During the review process, the program committee chairs will choose approximately 3% of submissions to receive an award. Among these chosen submissions, the separate Conference Awards Selection Committee will select the best submissions to receive a Best Paper Award (ca. 1% of total submissions), while a selection of the remaining submissions receive an Honorable Mention Award. Papers that receive an award will be marked in the program and authors will receive a certificate at the conference.

Best Papers

VR.net: A Real-world Large-scale Dataset for Virtual Reality Motion Sickness Research (Journal: P1422)

Elliott Wen, The University of Auckland; Chitralekha Gupta, National University of Singapore; Prasanth Sasikumar, National University of Singapore; Mark Billinghurst, University of South Australia; James Wilmott, Meta; Emily Skow, Meta; Arindam Dey, Meta; Suranga Nanayakkara, The University of Auckland

This paper introduces VR.net, a dataset with 165 hours of gameplay videos from 100 real-world games spanning 10 genres, evaluated by 500 participants. The dataset assigns 24 motion sickness-related labels per video frame. They are automatically extracted from 3D engines' rendering pipelines. VR.net's substantial scale, accuracy, and diversity present unmatched opportunities for VR motion sickness research and beyond.

Redirection Strategy Switching: Selective Redirection Controller for Dynamic Environment Adaptation (Journal: P1873)

Ho Jung Lee, Yonsei University; Sang-Bin Jeon, Yonsei University; Yong-Hun Cho, Korea University; In-Kwon Lee, Yonsei University

Selective Redirection Controller (SRC) is a novel approach to Redirected Walking (RDW) that dynamically switches between four redirection controllers (S2C, TAPF, ARC, SRL) based on the user's environment. Unlike traditional methods, SRC, trained by reinforcement learning, allows real-time controller switching to optimize the RDW experience. It's been evaluated through simulations and user studies, demonstrating a significant reduction in resets compared to conventional controllers. SRC's decision making is analysed using heat map visualization, allowing it to effectively exploit the advantages of each strategy. The result is a more immersive and seamless RDW experience that showcases SRC's innovative, contextual design.

The Differential Effects of Multisensory Attentional Cues on Task Performance in VR Depending on the Level of Cognitive Load and Cognitive Capacity (Journal: P1040)

Sihyun Jeong, KAIST; Jinwook Kim, KAIST; Jeongmi Lee, KAIST

Devising attentional cues that optimize VR task performance has become crucial. We investigated how the effects of attentional cues on task performance are modulated by the levels of cognitive load and cognitive capacity. Participants engaged in dual tasks under different levels of cognitive load while an attentional cue (visual, tactile, or visuotactile) was presented. The results showed that multi-sensory attentional cues are generally more effective than uni-sensory cues in enhancing task performance, but the benefit of multi-sensory cues increases with higher cognitive load and lower cognitive capacity. These findings provide practical implications for designing attentional cues to enhance VR task performance.

Evaluating Text Reading Speed in VR Scenes and 3D Particle Visualizations (Journal: P1072)

Johannes Novotny PhD, VRVis Zentrum für Virtual Reality und Visualisierung; David H. Laidlaw, Brown University

We report on the effects of text size and display parameters on reading speed and legibility in three state-of-the-art VR displays. Two are head-mounted displays, and one is Brown’s CAVE-like YURT. Our two perception experiments uncover limits where reading speed declines as the text size approaches the so-called critical print sizes (CPS) of individual displays. We observe an inverse correlation between display resolution and CPS, revealing hardware-specific limitations on legibility beyond display resolution, making CPS an effective benchmark for VR devices. Additionally, we report on the effects of text panel placement, orientation, and occlusion-reducing rendering methods on reading speeds in volumetric particle visualization.

Projection Mapping under Environmental Lighting by Replacing Room Lights with Heterogeneous Projectors (Journal: P1121)

Masaki Takeuchi, Osaka University; Hiroki Kusuyama, Osaka University; Daisuke Iwai, Osaka University; Kosuke Sato, Osaka University

Projection mapping (PM) typically requires a dark environment to achieve high-quality projections, limiting its practicality. In this paper, we overcome this limitation by replacing conventional room lighting with heterogeneous projectors. These projectors replicate environmental lighting by selectively illuminating the scene, excluding the projection target. Our contributions include a distributed projector optimization framework designed to effectively replicate environmental lighting and the incorporation of a large-aperture projector to reduce high-luminance emitted rays and hard shadows. Our findings demonstrate that our projector-based lighting system significantly enhances the contrast and realism of PM results.

Swift-Eye: Towards Anti-blink Pupil Tracking for Precise and Robust High-Frequency Near-Eye Movement Analysis with Event Cameras (Journal: P1220)

Tongyu Zhang, Shandong University; Yiran Shen, Shandong University; Guangrong Zhao, School of Software; Lin Wang, HKUST, GZ; Xiaoming Chen, Beijing Technology and Business University; Lu Bai, Shandong University; Yuanfeng Zhou, Shandong University

In this paper, we propose Swift-Eye, an offline precise and robust pupil estimation and tracking framework to support high-frequency near-eye movement analysis, especially when the pupil region is partially occluded. Swift-Eye is built upon the emerging event cameras to capture the high-speed movement of eyes in high temporal resolution. Then, a series of bespoke components are designed to generate high-quality near-eye movement video at a high frame rate over kilohertz and deal with the occlusion over the pupil caused by involuntary eye blinks. According to our extensive evaluations on EV-Eye, a large-scale public dataset for eye tracking using event cameras, Swift-Eye shows high robustness against significant occlusion.

Best Papers - Honorable Mentions

Robust Dual-Modal Speech Keyword Spotting for XR Headsets (Journal: P1317)

Zhuojiang Cai, Beihang University; Yuhan Ma, Beihang University; Feng Lu, Beihang University

While speech interaction finds widespread utility within the Extended Reality (XR) domain, conventional vocal speech keyword spotting systems continue to grapple with formidable challenges, including suboptimal performance in noisy environments, impracticality in situations requiring silence, and susceptibility to inadvertent activations when others speak nearby. These challenges, however, can potentially be surmounted through the cost-effective fusion of voice and lip movement information. Consequently, we propose a novel vocal-echoic dual-modal keyword spotting system for XR headsets. Experimental results demonstrate the promising performance of this dual-modal system across various challenging scenarios.

Instant Segmentation and Fitting of Excavations in Subsurface Utility Engineering (Journal: P1561)

Marco Stranner, Institute for Computer Graphics and Vision; Philipp Fleck, Graz University of Technology; Dieter Schmalstieg, Graz University of Technology; Clemens Arth, Graz University of Technology

AR for subsurface utility engineering (SUE) has benefited from recent advances in sensing hardware. In this work, we present a novel approach to automate the process of aligning existing SUE databases with measurements taken during excavation works, with the potential to correct the deviation from the as-planned to as-built documentation. Our segmentation algorithm performs infrastructure segmentation based on the live capture of an excavation on site. Our fitting approach correlates the inferred position and orientation with the existing digital plan and registers the as-planned model into the as-built state. We show the results of our proposed method on both synthetic data and a set of real excavations.

Analyzing user behaviour patterns in a cross-virtuality immersive analytics system (Journal: P1631)

Mohammad Rajabi Seraji, Simon Fraser University; Parastoo Piray, Simon Fraser University; Vahid Zahednejad, Simon Fraser University; Wolfgang Stuerzlinger, Simon Fraser University

Motivated by the recently discovered benefits of Cross-virtuality Immersive Analytics (XVA) systems, we developed HybridAxes, which allows users to transition seamlessly between the desktop and a virtual environment. Our user study shows that users prefer AR for exploratory tasks and the desktop for detailed tasks, indicating that these modes of an XVA system complement each other in enhancing the data analysis experience. Despite minor challenges in mode-switching, the system was well-received for its user-friendliness and engagement. Our research offers design insights, valuable directions for future cross-virtuality visual analytics systems, and identifies potential areas for further study.

Modeling the Impact of Head-Body Rotations on Audio-Visual Spatial Perception for Virtual Reality Applications (Journal: P1307)

Edurne Bernal-Berdun, Universidad de Zaragoza - I3A; Mateo Vallejo, Universidad de Zaragoza - I3A; Qi Sun, New York University; Ana Serrano, Universidad de Zaragoza; Diego Gutierrez, Universidad de Zaragoza

Proper synchronization of visual and auditory feedback is crucial for perceiving a coherent and immersive virtual reality (VR) experience. We investigate how audio-visual offsets and rotation velocities impact users' directional localization acuity during natural head-body rotations. Using psychometric functions, we model perceptual disparities and identify offset detection thresholds. Results show that target localization accuracy is affected by perceptual audio-visual disparities during head-body rotations when there is a stimuli-head relative motion. We showcase with a VR game how a compensatory approach based on our study can enhance localization accuracy by up to 40%. Similarly, we provide guidelines for enhancing VR content creation.

With or Without You: Effect of Contextual and Responsive Crowds on VR-based Crowd Motion Capture (Journal: P1727)

Tairan Yin, INRIA; Ludovic Hoyet, Inria; Marc Christie, IRISA; Marie-Paule R. Cani, Ecole Polytechnique, IP Paris; Julien Pettré, Inria

Capturing real crowd motions is challenging. VR helps by immersing users in simulated or motion-capture-based crowds. Users' motions can extend the crowd size using Record-and-Replay (2R), but these methods have limitations affecting data quality. We introduce contextual crowds, combining crowd simulation and 2R for consistent data. We present two strategies: Replace-Record-Replay (3R), where simulated agents are replaced by user data, and Replace-Record-Replay-Responsive (4R), where agents gain responsive capabilities. Evaluated in VR-replicated real-world scenarios, these paradigms yield more natural user behaviors, enhancing captured crowd data consistency.

Towards Co-operative Beaming Displays: Dual Steering Projectors for Extended Projection Volume and Head Orientation Range (Journal: P2043)

Hiroto Aoki, The University of Tokyo; Takumi Tochimoto, Tokyo Institute of Technology; Yuichi Hiroi, Cluster Inc.; Yuta Itoh, The University of Tokyo

This study tackles trade-offs in existing near-eye displays (NEDs) by introducing a beaming display with dual steering projectors. While the traditional NED faces challenges in size, weight, and user limitations, the beaming display separates the NED into a steering projector (SP) and a passive headset. To overcome issues with a single SP, dual projectors are distributed to extend head orientation. A geometric model and calibration method for multiple projectors are proposed. The prototype achieves precision (1.8 ∼ 5.7 mm) and delay (14.46 ms) at 1m, projecting images in the passive headset's area (20 mm × 30 mm) and enabling multiple users with improved presentation features.

BiRD: Using Bidirectional Rotation Gain Differences to Redirect Users during Back-and-forth Head Turns in Walking (Journal: P2113)

Sen-Zhe Xu, Tsinghua University; Fiona Xiao Yu Chen, Tsinghua University; Ran Gong, Tsinghua University; Fang-Lue Zhang, Victoria University of Wellingtong; Song-Hai Zhang, Tsinghua University

Redirected walking (RDW) facilitates user navigation within expansive virtual spaces despite the constraints of limited physical spaces. It employs discrepancies between human visual-proprioceptive sensations, known as gains, to enable the remapping of virtual and physical environments. In this paper, we explore how to apply rotation gain while the user is walking. We propose to apply a rotation gain to let the user rotate by a different angle when reciprocating from a previous head rotation, to achieve the aim of steering the user to a desired direction. To apply the gains imperceptibly based on such a Bidirectional Rotation gain Difference (BiRD), we conduct both measurement and verification experiments on the detection thresholds of the rotation gain for reciprocating head rotations during walking. Unlike previous rotation gains which are measured when users are turning around in place (standing or sitting), BiRD is measured during users’ walking. Our study offers a critical assessment of the acceptable range of rotational mapping differences for different rotational orientations across the user's walking experience, contributing to an effective tool for redirecting users in virtual environments.

Try This for Size: Multi-Scale Teleportation in Immersive Virtual Reality (Journal: P1016)

Tim Weissker, RWTH Aachen University; Matthis Franzgrote, RWTH Aachen University; Torsten Wolfgang Kuhlen, RWTH Aachen University

We present three novel teleportation-based techniques that enable users to adjust their own scale while traveling through virtual environments. Our approaches build on the extension of known teleportation workflows and suggest specifying scale adjustments either simultaneously with, as a connected second step after, or separately from the user's new horizontal position. The results of a two-part user study with 30 participants indicate that the simultaneous and connected specification paradigms are both suitable candidates for effective and comfortable multi-scale teleportation with nuanced individual benefits. Scale specification as a separate mode, on the other hand, was considered less beneficial.

Stepping into the Right Shoes: The Effects of User-Matched Avatar Ethnicity and Gender on Sense of Embodiment in Virtual Reality (Journal: P1126)

Tiffany D. Do, University of Central Florida; Camille Isabella Protko, University of Central Florida; Ryan P. McMahan, University of Central Florida

In many consumer VR applications, users embody predefined characters that offer minimal customization options, frequently emphasizing storytelling over choice. We investigated if matching a user's ethnicity and gender with their virtual self-avatar affects their affects their sense of embodiment in VR. A 2x2 experiment with diverse participants (n=32) showed matching ethnicity increased overall sense embodiment, irrespective of gender, impacting sense of appearance, response, and ownership. Our findings highlight the significance of avatar-user alignment for a more immersive VR experience.

Breaking the Isolation: Exploring the Impact of Passthrough in Shared Spaces on Player Performance and Experience in VR Exergames (Journal: P1232)

Zixuan Guo, Xi'an Jiaotong-Liverpool University; Hongyu Wang, Xi'an Jiaotong-Liverpool University; Hanxiao Deng, Xi'an Jiaotong-Liverpool University; Wenge Xu, Birmingham City University; Nilufar Baghaei, University of Queensland; Cheng-Hung Lo, Xi'an Jiaotong-Liverpool University; Hai-Ning Liang, Xi'an Jiaotong-Liverpool University

VR exergames boost physical activity but face challenges in shared spaces due to the presence of bystanders. Passthrough in VR enhances players' environmental awareness, offering a promising solution. This work explores its impact on player performance and experience in the following conditions: Space (Office vs. Corridor) and Passthrough Function (With vs. Without). Results show Passthrough improves performance and awareness while reducing immersion, especially benefiting higher self-consciousness players. Players typically favor open spaces that consider social acceptability issues, and Passthrough addresses concerns in both shared space types. Our findings offer insights for designing VR experiences in shared environments.

Spatial Contraction Based on Velocity Variation for Natural Walking in Virtual Reality (Journal: P2112)

Sen-Zhe Xu, Tsinghua University; Kui Huang, Tsinghua University; Cheng-Wei Fan, Tsinghua University; Song-Hai Zhang, Tsinghua University

Virtual Reality (VR) offers an immersive 3D digital environment, but enabling natural walking sensations without the constraints of physical space remains a technological challenge. This paper introduces "Spatial Contraction (SC)", an innovative VR locomotion method inspired by the phenomenon of Lorentz contraction in Special Relativity. Similar to the Lorentz contraction, our SC contracts the virtual space along the user's velocity direction in response to velocity variation. The virtual space contracts more when the user's speed is high, whereas minimal or no contraction happens at low speeds. We provide a virtual space transformation method for spatial contraction and optimize the user experience in smoothness and stability. Through SC, VR users can effectively traverse a longer virtual distance with a shorter physical walking. Different from locomotion gains, there is no inconsistency between the user's proprioception and visual perception in SC. SC is a general locomotion method that has no special requirements for VR scenes. The experimental results of live user studies in various virtual scenarios demonstrate that SC has a significant effect in reducing both the number of resets and the physical walking distance users need to cover. Furthermore, experiments have also demonstrated that SC has the potential for integration with the translation gain.

Best Posters & Honorable Mentions

The IEEE VR Best Poster Awards honors exceptional posters published and presented at the IEEE VR conference. During the review process, the best poster committee for IEEE VR consists of three distinguished members chosen by the Conference Awards Committee and Poster Chairs, which will select the best posters. Posters that receive an award will be marked in the program and authors will receive a certificate at the conference.

Best Posters

Aging Naturally: Virtual reality nature vs real-world nature's effects on executive functioning and stress recovery in older adults (ID: P1107)

Sara LoTemplio, Colorado State University; Sharde Johnson, Colorado State University; Michaela Rice, Colorado State University; Rachel Masters, Colorado State University; Sara-Ashley Collins, Colorado State University; Joshua Hofecker, Colorado State University; Jordan Rivera, Colorado State University; Dylan Schreiber, Colorado State University; Victoria Interrante, University of Minnesota; Francisco Raul Ortega, Colorado State University; Deana Davalos, Colorado State University

Development of Alzheimer's Dementia & other related dementias (ADRD) is characterized by decline in executive functioning (EF), and onset risk of ADRD is increased by stress. Previous work has shown that spending time in nature or virtual reality nature can improve EF and improve stress recovery in younger adults. Yet, little work has examined whether these benefits can extend to older adults. We examine how spending time in either nature or an equivalently designed virtual reality natural environment can affect EF and stress in older adults compared to a lab control condition.

Tremor Stabilization for Sculpting Assistance in Virtual Reality (ID: P1106)

Layla Erb, Augusta University; Jason Orlosky, Augusta University

This paper presents an exploration of assistive technology for virtual reality (VR) art, such as sculpting and ceramics. For many artists, tremors from Parkinsonian diseases can interfere with molding, carving, cutting, and modeling of different mediums for creating new sculptures. To help address this, we have developed a system that algorithmically stabilizes tremors to enhance the artistic experience for creators with physical impairments or movement disorder. In addition, we present a real-time sculpting application that allows us to measure differences in sculpting actions and a target object or shape.

Investigating Incoherent Depth Perception Features in Virtual Reality using Stereoscopic Impostor-Based Rendering (ID: P1041)

Kristoffer Waldow, TH Köln; Lukas Decker, TH Köln; Martin Mišiak, University of Würzburg; Arnulph Fuhrmann, TH Köln; Daniel Roth, Technical University of Munich; Marc Erich Latoschik, University of Würzburg

Depth perception is essential for our daily experiences, aiding in orientation and interaction with our surroundings. Virtual Reality allows us to decouple such depth cues mainly represented through binocular disparity and motion parallax. Dealing with fully-mesh-based rendering methods these cues are not problematic as they originate from the object's underlying geometry. However, manipulating motion parallax, as seen in stereoscopic imposter-based rendering, raises questions about visual errors and perceived 3-dimensionality. Therefore, we conducted a user experiment to investigate how varying object sizes affect such visual errors and perceived 3-dimensionality, revealing an interestingly significant negative correlation and new assumptions about visual quality.

How Long Do I Want to Fade Away? The Duration of Fade-To-Black Transitions in Target-Based Discontinuous Travel (Teleportation) (ID: P1121)

Matthias Wölwer, University of Trier; Benjamin Weyers, Trier University; Daniel Zielasko, University of Trier

A fade-to-black animation enhances the transition during teleportation, yet its duration has not been systematically explored even though it is one of the central parameters. To fill this gap, we conducted a small study to determine a preferred duration. We find a short duration of 0.3s to be the average preference, contrasting durations used previously in the literature. This research contributes to the systematic parameterization of discontinuous travel.

The Influence of Metaverse Environment Design on Learning Experiences in Virtual Reality Classes: A Comparative Study (ID: P1305)

Valentina Uribe, Universidad de los Andes; Vivian Gómez, Universidad de los Andes; Pablo Figueroa, Universidad de los Andes

In this study, we investigate learning and the quality of the classroom experience by conducting classes in four metaverse environments: Workrooms, Spatial, Mozilla Hubs, and Arthur. Using questionnaires, we analyze factors like avatars, spatial layout, mobility, and additional functions' influence on concentration, usability, presence, and learning. Despite minimal differences in learning outcomes, significant variations in classroom experience emerged. Particularly, metaverses with restricted movement and functions showed heightened immersion, concentration, and presence. Additionally, our findings underscore the beneficial influence of avatars featuring lifelike facial expressions in improving the overall learning encounter.

Brain Dynamics of Balance Loss in Virtual Reality and Real-world Beam Walking (ID: P1141)

Amanda Studnicki, University of Florida; Ahmed Rageeb Ahsan, University of Florida; Eric Ragan, University of Florida; Daniel P. Ferris, University of Florida

Virtual reality (VR) aims to replicate the sensation of a genuine experience through the integration of realism, presence, and embodiment. In this study, we used mobile electroencephalography to quantify differences in anterior cingulate brain activity, an area involved in error monitoring, with and without VR during a challenging balance task to discern the factors contributing to VR's perceptual shortcomings. We found a major delay in the anterior cingulate response to self-generated loss of balance in VR compared to the real world. We also found a robust response in the anterior cingulate when loss of balance was generated by external disturbance.

Best Poster - Honorable Mentions

Evaluation of Monocular and Binocular Contrast Sensitivity on Virtual Reality Head-Mounted Displays (ID: P1298)

Khushi Bhansali, Cornell University; Miguel Lago, U.S. FDA; Ryan Beams, Food and Drug Administration; Chumin Zhao, CDRH, United States Food and Drug Administration

Virtual reality (VR) creates an immersive experience by rendering a pair of graphical views on a head-mounted display (HMD). However, image quality assessment on VR HMDs has been primarily limited to monocular optical bench measurements on a single eyepiece. We begin to bridge the gap between monocular and binocular image quality evaluation by developing a WebXR test platform to perform human observer experiments. Specifically, monocular and binocular contrast sensitivity functions (CSFs) are obtained using varied interpupillary distance (IPD) conditions. A combination of optical image quality characteristics and binocular summation can potentially predict the binocular contrast sensitivity on VR HMDs.

AgileFingers: Authoring AR Character Animation Through Hierarchical and Embodied Hand Gestures (ID: P1288)

Yue Lin, The Hong Kong University of Science and Technology (Guangzhou); Yudong Huang, The Hong Kong University of Science and Technology (Guangzhou); David Yip, The Hong Kong University of Science and Technology; Zeyu Wang, The Hong Kong University of Science and Technology (Guangzhou)

We present AgileFingers, a hand gesture-based solution for authoring AR character animation based on a mobile device. Our work initially categorizes four major types of animals under Vertebrata. We conducted a formative study on how users construct hierarchical relationships in full-body skeletal animation and potential hand structure mapping rules. Informed by the study, we developed a hierarchical segmented control system, which enables novice users to manipulate full-body 3D characters with unimanual gestures sequentially. Our user study reveals the ease of use, intuitiveness, and high adaptability of the AgileFingers system across various characters. 

Repeat Body-Ownership Illusions in Commodity Virtual Reality (ID: P1215)

Pauline W Cha, Davidson College; Tabitha C. Peck, Davidson College

Virtual self-avatars have been shown to produce the Proteus effect, however limited work investigates the subjective sense of embodiment using commodity virtual reality systems. In this work, we present results from a pilot experiment where participants are given a self-avatar in a simple virtual experience while wearing a cardboard head-mounted display. Participants then repeat the experience five days later. Overall, subjective embodiment scores are similar to those reported in experience using higher-fidelity systems. However, the subjective sense of embodiment significantly lowered from trial one to trial two.

Evaluation of Shared-Gaze Visualizations for Virtual Assembly Tasks (ID: P1060)

Daniel Alexander Delgado, University of Florida; Jaime Ruiz, University of Florida

Shared-gaze visualizations (SGV) allow collocated collaborators to understand each other's attention and intentions while working jointly in an augmented reality setting. However, prior work has overlooked user control and privacy over how gaze information can be shared between collaborators. In this abstract, we examine two methods for visualizing shared-gaze between collaborators: gaze-hover and gaze-trigger. We compare the methods with existing solutions through a paired-user evaluation study in which participants participate in a virtual assembly task. Finally, we contribute an understanding of user perceptions, preferences, and design implications of shared-gaze visualizations in augmented reality.

Redirected Walking vs. Omni-Directional Treadmills: An Evaluation of Presence (ID: P1301)

Raiffa Syamil, University of Central Florida; Mahdi Azmandian, Sony Interactive Entertainment; Sergio Casas-Yrurzum, University of Valencia; Pedro Morillo, University of Valencia; Carolina Cruz-Neira, University of Central Florida

Omni-Directional Treadmills (ODT) and Redirected Walking (RDW) seem suitable for eliciting presence through a full-body walking experience, however both present unique mechanisms that can affect users' presence, comfort, and overall preference. To measure this effect, we conducted a counterbalanced within-subjects user study with 20 participants. Participants wore a wireless VR headset and experienced a tour of a virtual art museum, once using RDW and another time using a passive, slip-based ODT. Both solutions elicit similar amounts of presence, however RDW is perceived as more natural and is the preferred choice of the participants.

Designing Non-Humanoid Virtual Assistants for Task-Oriented AR Environments (ID: P1094)

Bettina Schlager, Columbia University; Steven Feiner, Columbia University

In task-oriented Augmented Reality (AR), humanoid Embodied Conversational Agents can enhance the feeling of social presence and reduce mental workload. Yet, such agents can also introduce social biases and lead to distractions. This presents a challenge for AR applications that require the user to concentrate mainly on a task environment. To address this, we introduce a non-humanoid virtual assistant designed for minimal visual intrusion in AR. Our approach aims to enhance a user's focus on the tasks they need to perform. We explain our design choices based on previously published guidelines and describe our prototype implemented for an optical--see-through headset.

Best Research Demos & Honorable Mentions

The IEEE VR Best Research Demo Awards honors exceptional research demos published and presented at the IEEE VR conference. The IEEE VR Research Demonstration Chairs rank the accepted demos and recommend approximately 10% of all demos for an award. The best research demo committee for IEEE VR consists of three distinguished members chosen by the Conference Awards Committee Chairs and the Research Demonstration Chairs. This committee selects one of the demos for the Best Research Demo Award and one for the Honorable Mention Award. The corresponding authors will receive a certificate at the conference.

Best Research Demo

Navigating Realities: Assessing Cross-Reality Transitions Through a Spatial Memory Game in VR and AR Environments (ID: PO1015)

Nico Feld, Trier University; Pauline Bimberg, University of Trier; Benjamin Weyers, Trier University; Daniel Zielasko, University of Trier

This tech demo offers an immersive exploration of the most prominent scene transitions within the Reality-Virtuality Continuum (RVC). It delves into the seamless integration of real and virtual worlds, showcasing a spectrum of environments ranging from entirely real to fully virtual and various transitions to switch between them. Our innovative approach centers around an engaging cross-environmental spatial memory game. This game is not just a playful experience but a carefully crafted task d...

Best Research Demo - Honorable Mention

GPT-VR Nexus: ChatGPT-Powered Immersive Virtual Reality Experience (ID: PO1060)

Jiangong Chen, Pennsylvania State University; Tian Lan, George Washington University; Bin Li, Pennsylvania State University

The fusion of generative Artificial Intelligence (AI) like ChatGPT and Virtual Reality (VR) can unlock new interaction capabilities through natural language. We introduce GPT-VR Nexus, a novel framework creating a truly immersive VR experience driven by an underlying generative AI engine. It employs a two-step prompt strategy and robust post-processing procedures, without fine-tuning the complex AI model. Our experimental results show quick responses to various user audio requests/inputs.

Best 3DUI Contest Demos & Honorable Mentions

The IEEE VR Best 3DUI Contest Submission Awards honors exceptional 3DUI contest submissions published and presented at the IEEE VR conference. The 3DUI contest chairs select one of the submissions for the Best 3DUI Contest Submission Award and one for the Honorable Mention Award. The final decision is based on a combination of the reviews’ scores, scores from experts testing the contest submission during the conference, and the audience scores. The winning team with the highest score will be awarded. Authors will receive a certificate at the conference.

Best 3DUI Contest Demo

Will The Apple Fall? A VR Gravity Calculator Through Controller Movement Tracking and Gaze Interaction (ID: 1010)

Barnabas Lee, Independent; Miss Shu Wei, University of Oxford

Best 3DUI Contest Demo - Honorable Mention

Beyond Euclid: An Educational Virtual Reality Journey into Spherical Geometry (ID: 1002)

Agapi Chrysanthakopoulou, University of Patras; Theofilos Chrysikopoulos, University of Patras; Leandros Nikolaos Arvanitopoulos, University of Patras; Kostantinos Moustakas, University of Patras

Best Doctoral Consortium Paper

The IEEE VR Best Doctoral Consortium (DC) Paper Awards honors exceptional DC papers published and presented at the IEEE VR conference. The best DC paper committee consists of three distinguished members chosen by the Conference Awards Committee Chairs and the DC chairs. The DC chairs recommend 20% of all DC papers for such an award. The best DC committee selects one of these DC papers for Best DC Paper Award. The DC paper that receives the award will be marked in the program and the author will receive a certificate at the conference.

Toward Realistic 3D Avatar Generation with Dynamic 3D Gaussian Splatting for AR/VR Communication (ID: 1098)

Author: Hail Song , Korea Advanced Institute of Science and Technology, Republic of Korea, Mentor: Jason Orlosky

Realistic avatars are fundamental for immersive experiences in Augmented Reality (AR) and Virtual Reality (VR) environments. In this work, we introduce a novel approach for avatar generation, combining 3D Gaussian Splatting with the parametric body model, SMPL. This methodology overcomes the inefficiencies of traditional image/video-based avatar creation, which is often slow and requires high computing resources. The integration of 3D Gaussian Splatting for representing human avatar offers realistic and real-time rendering for AR/VR applications. We also conducted preliminary tests to verify the quality of avatar representation using 3D Gaussian Splatting. These tests, displayed alongside outcomes from existing methods, demonstrate the potential of this research to significantly contribute to the creation of realistic avatars in the future. Additionally, several key discussions are presented, essential for developing and evaluating the system and providing valuable insights for future research.

Best Paper Presentations & Honorable Mentions

The IEEE VR Best Presentation Awards honor excellent, interesting, and stimulating presentations of research papers at the IEEE VR conference. During the conference, the audience can give a vote for each presentation that they think deserves an award. Approximately 3% of presentations with the highest number of votes receive an award. Among these selected presentations, the top 1% regarding the number of votes, will receive a Best Presentation Award, while the remaining presentations receive an Honorable Mention Award.

Best Paper Presentations

The Effects of Auditory, Visual, and Cognitive Distractions on Cybersickness in Virtual Reality (ID: P3014)

Rohith Venkatakrishnan, School of Computing, Clemson University, USA; Roshan Venkatakrishnan, School of Computing, Clemson niversity, USA; Balagopal Raveendranath, Department of Psychology, Clemson University, USA; Dawn M. Sarno, Department of Psychology, Clemson University, USA; Andrew C. Robb, School of Computing, Clemson University, USA; Wen-Chieh Lin, Department of Computer Science, National Yang Ming Chiao Tung University, Taiwan; Sabarish V. Babu, School of Computing, Clemson University, USA

Cybersickness (CS) is one of the challenges that has hindered the widespread adoption of Virtual Reality (VR). Consequently, researchers continue to explore novel means to mitigate the undesirable effects associated with this affliction, one that may require a combination of remedies as opposed to a solitary stratagem. Inspired by research probing into the use of distractions as a means to control pain, we investigated the efficacy of this countermeasure against CS, studying how the introduction of temporally time-gated distractions affects this malady during a virtual experience featuring active exploration. Downstream of this, we discuss how other aspects of the VR experience are affected by this intervention. We discuss the results of a between-subjects study manipulating the presence, sensory modality, and nature of periodic and short-lived (5-12 seconds) distractor stimuli across 4 experimental conditions: (1) no-distractors (ND); (2) auditory distractors (AD); (3) visual distractors (VD); (4) cognitive distractors (CD). Two of these conditions (VD and AD) formed a yoked control design wherein every matched pair of ‘seers’ and ‘hearers’ was periodically exposed to distractors that were identical in terms of content, temporality, duration, and sequence. In the CD condition, each participant had to periodically perform a 2-back working memory task, the duration and temporality of which was matched to distractors presented in each matched pair of the yoked conditions. These three conditions were compared to a baseline control group featuring no distractions. Results indicated that the reported sickness levels were lower in all three distraction groups in comparison to the control group. The intervention was also able to both increase the amount of time users were able to endure the VR simulation, as well as avoid causing detriments to spatial memory and virtual travel efficiency. Overall, it appears that it may be possible to make users less consciously aware and bothered by the symptoms of CS, thereby reducing its perceived severity.

The Effects of Secondary Task Demands on Cybersickness in Active Exploration Virtual Reality Experiences (ID: P1769)

Rohith Venkatakrishnan, Clemson University; Roshan Venkatakrishnan, Clemson University; Balagopal Raveendranath, Clemson University; Ryan Canales, Clemson University; Dawn M. Sarno, Clemson University; Andrew Robb, Clemson University; Wen-Chieh Lin, National Yang Ming Chiao Tung University; Sabarish V. Babu, Clemson University

During navigation, users often engage in additional tasks that require attentional resources. This work investigated how the attentional demands of secondary tasks performed during exploration affect cybersickness in virtual reality. We manipulated a secondary task's demand across two levels and studied its effects on sickness in two provocative experiences. Results revealed that increased secondary task demand generally exacerbated sickness levels, further vitiating spatial memory and navigational performance. In light of research demonstrating the use of distractions to counteract sickness, our results suggest the existence of a threshold beyond which distractions can reverse from being sickness-reducing to sickness-inducing.

Best Paper Presentation - Honorable Mentions

BOXRR-23: 4.7 Million Motion Capture Recordings from 105,000 XR Users (ID: P1654)

Vivek C Nair, UC Berkeley; Wenbo Guo, Purdue University; Rui Wang, Carnegie Mellon University; James F. O'Brien, UC Berkeley; Louis Rosenberg, Unanimous AI; Dawn Song, UC Berkeley

Extended reality (XR) devices such as the Meta Quest and Apple Vision Pro have seen a recent surge in attention, with motion tracking "telemetry" data lying at the core of nearly all XR and metaverse experiences. Researchers are just beginning to understand the implications of this data for security, privacy, usability, and more, but currently lack large-scale human motion datasets to study. The BOXRR-23 dataset contains 4,717,215 motion capture recordings, voluntarily submitted by 105,852 XR device users from over 50 countries. BOXRR-23 is over 200 times larger than the largest existing motion capture research dataset and uses a new, highly efficient and purpose-built XR Open Recording (XROR) file format.

Investigating the Effects of Avatarization and Interaction Techniques on Near-field Mixed Reality Interactions with Physical Components (ID: P1482)

Roshan Venkatakrishnan, Clemson University; Rohith Venkatakrishnan, Clemson University; Ryan Canales, Clemson University; Balagopal Raveendranath, Clemson University; Christopher Pagano, Clemson University; Andrew Robb, Clemson University; Wen-Chieh Lin, National Yang Ming Chiao Tung University; Sabarish V. Babu, Clemson University

Mixed reality experiences typically involve users interacting with a combination of virtual and physical components. In an attempt to understand how such interactions can be improved, we investigated how avatarization, the physicality of the interacting components, and interaction techniques affect the user experience. Results indicate that accuracy is more when the components are virtual rather than physical because of the increased salience of the task-relevant information. Furthermore, the relationship between avatarization and interaction techniques dictate how usable mixed reality interactions are deemed to be. This study provides key insights for optimizing mixed reality interactions towards immersive and effective user experiences.

EyeShadows: Peripheral Virtual Copies for Rapid Gaze Selection and Interaction (ID: P1153)

Jason Orlosky, Augusta University; Chang Liu, Kyoto University Hospital; Kenya Sakamoto, Osaka University; Ludwig Sidenmark, University of Toronto; Adam Mansour, Augusta University

In this paper, we present EyeShadows, an eye gaze-based selection system that takes advantage of peripheral copies of items that allow for quick selection and manipulation of an object or corresponding menus. This method is compatible with a variety of different selection tasks and controllable items, avoids the Midas touch problem, does not clutter the virtual environment, and is context sensitive. We have implemented and refined this selection tool for VR and AR, including testing with optical and video see-through displays. We demonstrate that EyeShadows can also be used for a wide range of AR and VR applications, including manipulation of sliders or analog elements.

An Empirical Evaluation of the Calibration of Auditory Distance Perception under Different Levels of Virtual Environment Visibilities (ID: P1669)

Wan-Yi Lin, National Yang Ming Chiao Tung University; Rohith Venkatakrishnan, University of Florida; Roshan Venkatakrishnan, University of Florida; Sabarish V. Babu, Clemson University; Christopher Pagano, Clemson University; Wen-Chieh Lin, National Yang Ming Chiao Tung University

We investigated if perceptual learning through carryover effects of calibration occurs in different levels of a virtual environment’s visibility. Users performed an auditory depth judgment task over several trials in which they walked where they perceived an aural sound to be. This task was sequentially performed in the pretest, calibration, and posttest phases. Feedback on the perceptual accuracy of distance estimates was only provided in the calibration phase. We found that auditory depth estimates, obtained using an absolute measure, can be calibrated to become more accurate and that environments visible enough to reveal their extent may contain visual information that users attune to in scaling aurally perceived depth.

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Photonics West Best Paper and Best Presentation Awards

Jump to:   BiOS Awards | LASE Awards | OPTO Awards

Application track best paper award winners

Thank you to the committee and chairs for reviewing and selecting the conference award recipients:

BiOS best paper award winners

LASE best paper award winners

OPTO best paper award winners

• Best Presentation Award

The Best Presentation Award celebrates the most inspiring and effective presentations, that are delivered by impactful, confident and engaging speakers.

Celebrating your great insights

At ESOMAR events, the insights and analytics community presents some of the most though-provoking and impactful projects undertaken across the world. A vast diversity of topics and impact are showcased through countless scientific papers and inspiring presentations.

We celebrate these stellar event moments through a series of awards including our Best Presentation Award which celebrates the speaker(s) who best inspire our event attendees and secure their votes.

What's the prize?

If you're out to build your personal brand, the Best Presentation Award is a real opportunity to stand out in front of business leaders and data, research and insights professionals from all over the world. Award winners get a number of perks including:

Exposure during the event to make your pitch and full presentation

Exposure of your performances on ESOMAR's social media and digital channels

Recognition by the industry when included in your CV or resume.

How to win the Award

Who can enter.

Your presentation needs to meet the following criteria:

Your paper is selected by a programme committee for presentation at one of our eligible events

Your presentation must inspire our event attendees

In addition, the Jury may take into account the extent to which the paper is useful to support our championing of insights, or deals with problems facing insights and analytics worldwide, in line with ESOMAR principles.

How do you enter?

The first step to becoming a nominee is to have your paper selected to be presented at one of our eligible events.

All selected speakers are automatically entered as nominees for event attendees to vote. To secure those votes they must put all their efforts in making a great, inspiring presentation.

2024 Award Winners

The Era of Pet Humanization Constanza Cilley, Voices Consultancy, Argentina

Art & Science of Innovation - Chicago

When Gen AI Meets Gen Z Adrian Terron, Tata Group, India

How it happens during our events

To earn the best presentation award, you must first be selected to speak at one of our eligible events. Check out the speaking opportunities and submit your paper for consideration by our programme committees.

Once you've been selected to speak at one of our eligible events, the pressure is on to make a big splash at the event. Attendees have the final say and they're looking for inspiring and engaging presentations that make them go wow. That's your challenge!

During the event, attendees get to vote their appreciation for your presentation alongside all of the other presentations during the same event. It's the presentation with the best score that gets the award.

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Kassas and Student Team Win Four Best Paper Presentation Awards

Zak Kassas , a Buckeye Engineering professor, and his students earned four best paper presentation awards at the Institute of Navigation Global Navigation Satellite Systems Conference ( ION GNSS+ ), held in Denver, Colorado. The research collectively pursues novel navigation approaches for ground vehicles, unmanned aerial vehicles (UAVs), and high-altitude aircraft, by exploiting signals from low Earth orbit (LEO) satellite signals (e.g., SpaceX’s Starlink) and cellular towers.

The first paper, titled “ Joint detection and tracking of unknown beacons for navigation with 5G signals and beyond ,” was co-authored by Electrical and Computer Engineering Professor Zak Kassas and his Ph.D. student Mohammad Neinavaie. The research established the theoretical foundations of a novel framework capable of jointly detecting and tracking unknown beacons of terrestrial signals. Experimental results demonstrated the efficacy of the established theory, showing a UAV and a ground vehicle successfully detecting unknown signals in the environment (from cellular 4G and 5G towers), tracking the signals, and navigating the vehicles with these signals.

The second paper, titled “ Blind receiver for LEO beacon estimation with application to UAV carrier phase differential navigation ,” was co-authored by Kassas and his Ph.D. student Sharbel Kozhaya. It proposed an innovative receiver design that can blindly estimate unknown signals transmitted by low Earth orbit (LEO) satellites. Experimental results showed successful blind acquisition and tracking of Orbcomm LEO satellites, which enable a UAV to navigate with these signals.

The third paper, titled “ Protecting the skies: GNSS-less aircraft navigation with terrestrial cellular signals of opportunity ,” was co-authored by Kassas, a past student, and collaborators from the U.S. Air Force. It showcased revolutionary results from a joint experiment conducted by Kassas’ Autonomous Systems Perception, Intelligence, and Navigation ( ASPIN ) Laboratory and the U.S. Air Force. The results demonstrated the tremendous promise of cellular signals as a reliable back to GPS for high-altitude aircraft navigation. ASPIN’s state-of-the-art cognitive software-defined receivers (SDRs) showed that hundreds of cellular signals can be acquired and tracked at high altitudes (more than 23,000 ft above ground level) and from cellular towers more than 100 km away. The paper also showed meter-level accurate aircraft navigation with only cellular signals over trajectories exceeding 50 km.

The fourth paper, titled “ Observability analysis of opportunistic receiver localization with LEO satellite pseudorange measurements ,” was co-authored by Kassas and his past student. It analyzed the observability of receiver localization with signals from a single LEO satellite. Experimental results showed a receiver localizing itself with signals from a single Starlink LEO satellite and a single Orbcomm LEO satellite. The results demonstrated the theoretical predictions of the paper’s observability analysis.

“It is fulfilling to see our results get recognized by the scientific community,” said Kassas. “ION GNSS+ is the largest annual positioning, navigation, and timing (PNT) conference, and the sessions in which these papers won the awards comprised papers from highly-respected research groups. Aside from these awards, it was particularly rewarding to witness several papers and industrial products at the conference building on ASPIN’s findings from the past few years. I’m very grateful to the Office of Naval Research (ONR), Department of Transportation (DOT), Air Force Office of Scientific Research (AFOSR), National Science Foundation (NSF), and Sandia National Laboratories for supporting our research.”

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IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2020

08-11 september 2020, vienna, austria.

Best paper and best presentations

ETFA 2020 is proud to announce the best paper and best presentation awards.

A total of 2 regular/special session best papers and 2 work-in-progress best papers were awarded.

The best presentations were determined at the end of each session by public real-time vote among the audience, both onsite and remote. We used Mentimeter as online voting tool. Below you find the winners of each session. For the WiP sessions, given that they had more papers, we show the winners and the two runner-ups. Online voting was a new experience for ETFA participants and provided a lot of fun and engagement no matter where they joined the conference.

Best Paper Awards

Best Paper Presentations on Tuesday

Best paper presentations on wednesday, best paper presentations on thursday, best paper presentations on friday.

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Association for the Advancement of Artificial Intelligence

AAAI Conference Paper Awards and Recognition

The AAAI Conference on Artificial Intelligence (formerly the AAAI National Conference on Artificial Intelligence) honors papers that exemplify the highest standards in technical contribution and exposition. During the blind review process, members of the Program Committee recommend papers to consider for the Outstanding Paper Award in the main technical track and special tracks, as indicated. In 2021, an additional category of Distinguished Papers was added for special recognition.

Past Recipients

Aaai-23 outstanding paper award.

Misspecification in Inverse Reinforcement Learning

Joar Skalse and Alessandro Abate

AAAI-23 Distinguished Paper Award

DropMessage: Unifying Random Dropping for Graph Neural Networks

Taoran Fang, Zhiqing Xiao, Chunping Wang, Jiarong Xu, Xuan Yang, Yang Yang

Two Heads are Better than One: Image-Point Cloud Network for Depth-Based 3D Hand Pose Estimation

Pengfei Ren, Yuchen Chen, Jiachang Hao, Haifeng Sun, Qi Qi, Jingyu Wang, Jianxin Liao

Neural Architecture Search for Wide Spectrum Adversarial Robustness

Zhi Cheng, Yanxi Li, Minjing Dong, Xiu Su, Shan You, Chang Xu

CowClip: Reducing CTR Prediction Model Training Time from 12 hours to 10 minutes on 1 GPU

Zangwei Zheng, Pengtai Xu, Xuan Zou, Da Tang, Zhen Li, Chenguang Xi, Peng Wu, Leqi Zou, Yijie Zhu, Ming Chen, Xiangzhuo Ding, Fuzhao Xue, Ziheng Qin, Youlong Cheng, Yang You

DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification

Chengliang Liu, Jie Wen, Xiaoling Luo, Chao Huang, Zhihao Wu, Yong Xu

Exploring Tuning Characteristics of Ventral Stream’s Neurons for Few-Shot Image Classification

Lintao Dong, Wei Zhai Zheng-Jun Zha

MaskBooster: End-to-End Self-Training for Sparsely Supervised Instance Segmentation

Shida Zheng, Chenshu Chen, Xi Yang, Wenming Tan

SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification       

Tianci Liu, Haoyu Wang, Yaqing Wang, Xiaoqian Wang, Lu Su, Jing Gao

XRand: Differentially Private Defense against Explanation-Guided Attacks           

Truc Nguyen, Phung Lai, Hai Phan, My T. Thai

Clustering What Matters: Optimal Approximation for Clustering with Outliers   

Akanksha Agrawal, Tanmay Inamdar, Saket Saurabh, Jie Xue

Robust Average-Reward Markov Decision Processes      

Yue Wang, Alvaro Velasquez, George Atia, Ashley Prater-Bennette, Shaofeng Zou

Efficient Answer Enumeration in Description Logics with Functional Roles

Carsten Lutz, Marcin Przybylko

AAAI Outstanding Student Papers

In 2022, an additional category of Distinguished Papers was added for special recognition.

Decorate the Newcomers: Visual Domain Prompt for Continual Test Time Adaptation

Yulu Gan, Yan Bai, Yihang Lou, Xianzheng Ma, Renrui Zhang, Nian Shi, Lin Luo

Student Abstract Program Awards

Best Student Abstract: TA-DA: Topic-Aware Domain Adaptation for Scientific Keyphrase Identification and Classification Răzvan-Alexandru Smădu, George-Eduard Zaharia, Andrei-Marius Avram, Dumitru-Clementin Cercel, Mihai Dascalu and Florin Pop

Honorable Mentions: On the Relation between Distributionally RobusAnti-Drifting Feature Selection via Deep Reinforcement Learning Aoran Wang, Hongyang Yang, Feng Mao, Zongzhang Zhang, Yang Yu and Xiaoyang Liu

Can Graph Neural Networks Learn to Solve the MaxSAT Problem?

Minghao Liu, Pei Huang, Fuqi Jia, Fan Zhang, Yuchen Sun, Shaowei Cai, Feifei Ma and Jian Zhang

2022 Best Demonstration Award

A Demonstration of Compositional, HierSudoku Assistant – An AI-powered app to help solve pen-and-paper Sudokus Tias Guns, Emilio Gamba, Maxime Mulamba Ke Tchomba, Ignace Bleukx, Senne Berden and Milan Pesa

AAAI-22 Outstanding Paper Award

Online Certification of Preference-based Fairness for Personalized Recommender Systems Virginie Do, Sam Corbett-Davies, Jamal Atif, Nicolas Usunier

Honorable Mention: Bayesian Persuasion in Sequential Decision-Making Jiarui Gan, Rupak Majumdar, Goran Radanovic, Adish Singla

Honorable Mention: Operator-Potential Heuristics for Symbolic Search Daniel Fišer, Alvaro Torralba, Joerg Hoffmann

AAAI Distinguished Papers

In 2021, an additional category of Distinguished Papers was added for special recognition.

AAAI-22 Distinguished Papers AlphaHoldem: High-Performance Artificial Intelligence for Heads-Up No-Limit Poker via End-to-End Reinforcement Learning Enmin Zhao, Renye Yan, Jinqiu Li, Kai Li, Junliang Xing

Certified Symmetry and Dominance Breaking for Combinatorial Optimisation Bart Bogaerts, Stephan Gocht, Ciaran McCreesh, Jakob Nordström

Online Elicitation of Necessarily Optimal Matchings Jannik Peters

Sampling-Based Robust Control of Autonomous Systems with Non-Gaussian Noise Thom S. Badings, Alessandro Abate, Nils Jansen, David Parker, Hasan A. Poonawala, Marielle Stoelinga

Subset approximation of Pareto Regions with Bi-objective A* Jorge A. Baier, Carlos Hernández, Nicolás Rivera

The SoftCumulative Constraint with Quadratic Penalty Yanick Ouellet, Claude-Guy Quimper

Outstanding Student Paper InfoLM: A New Metric to Evaluate Summarization & Data2Text Generation Pierre Colombo, Chloé Clavel, Pablo Piantanida

Honorable Mention: Compilation of Aggregates in ASP Systems Giuseppe Mazzotta, Francesco Ricca, Carmine Dodaro

Honorable Mention: Entropy estimation via normalizing flow Ziqiao Ao, Jinglai Li

Best Student Abstract: Annotation Cost-Sensitive Deep Active Learning with Limited Data Renaud Bernatchez, Audrey Durand and Flavie Lavoie-Cardinal

Honorable Mention: On the Relation between Distributionally Robust Optimization and Data Curation Agnieszka Słowik and Leon Bottou

A Demonstration of Compositional, Hierarchical Interactive Task Learning Aaron Mininger, John Laird

AAAI-21 Outstanding Paper Award

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li, Hui Xiong, Wancai Zhang

Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory Stefanos Leonardos, Georgios Piliouras

Honorable Mention: Learning from eXtreme Bandit Feedback Romain Lopez, Inderjit S. Dhillon, Michael Jordan

Honorable Mention: Self-Attention Attribution: Interpreting Information Interactions Inside Transformer Yaru Hao, Li Dong, Furu Wei, Ke Xu

AAAI-21 Outstanding Paper Award: Special Track on AI for Social Impact

Mitigating Political Bias in Language Models through Reinforced Calibration Ruibo Liu, Chenyan Jia, Jason W Wei, Guangxuan Xu, Lili Wang, Soroush Vosoughi

Honorable Mention: Dual-Mandate Patrols: Multi-Armed Bandits for Green Security Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe

AAAI-21 Distinguished Papers

IQ – Incremental Learning for Solving QSAT Thomas L Lee, Viktor Tóth, Sean B Holden

Ethically Compliant Sequential Decision Making Justin Svegliato, Samer Nashed, Shlomo Zilberstein

On the Tractability of SHAP Explanations Guy Van den Broeck, Anton Lykov, Maximilian Schleich, Dan Suciu

Expected Eligibility Traces Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel, Andre Barreto, David Silver, Diana Borsa

Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs Marcel Wienöbst, Max Bannach, Maciej Liskiewicz

Self-Supervised Multi-View Stereo via Effective Co-Segmentation and Data-Augmentation Hongbin Xu, Zhipeng Zhou, Yu Qiao, Wenxiong Kang, Qiuxia Wu

AAAI-20 Outstanding Paper Award

WinoGrande: An Adversarial Winograd Schema Challenge at Scale Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi

Honorable Mention: A Unifying View on Individual Bounds and Heuristic Inaccuracies in Bidirectional Search Vidal Alcazar, Pat Riddle, Mike Barley

AAAI-20 Outstanding Student Paper Award

Fair Division of Mixed Divisible and Indivisible Goods Xiaohui Bei, Zihao Li, Jinyan Liu, Shengxin Liu, Xinhang Lu

Honorable Mention: Lifelong Learning with a Changing Action Set Yash Chandak, Georgios Theocharous, Chris Nota, Philip S. Thomas

AAAI-20 Outstanding Paper Award: Special Track on AI for Social Impact

A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning Kevin Fauvel, Daniel Balouek-Thomert, Diego Melgar, Pedro Silva, Anthony Simonet, Gabriel Antoniu, Alexandru Costan, Véronique Masson, Manish Parashar, Ivan Rodero, Alexandre Termier

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Automatic Invention of Integer Sequences Simon Colton and Alan Bundy, University of Edinburgh; Toby Walsh, University of York

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Local Search Characteristics of Incomplete SAT Procedures Dale Schuurmans and Finnegan Southey, University of Waterloo

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A Practical Algorithm for Finding Optimal Triangulations Kirill Shoikhet and Dan Geiger, Technion, Israel

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Verification of Knowledge Bases Based on Containment Checking Alon Y. Levy, AT&T Research and Marie-Christine Rousset, University of Paris-Sud

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Qualitative Results Concerning the Utility of Explanation-Based Learning Steven Minton, Carnegie Mellon University

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Curing Anomalous Extensions Paul Morris, IntelliCorp

Non-Deterministic Lisp with Dependency-directed Backtracking Ramin Zabih, David McAllester, and David Chapman, MIT Artificial Intelligence Laboratory

Defining Operationality for Explanation-based Learning Richard M. Keller, Rutgers University

Word-Order Variation in Natural Language Generation Aravind K. Joshi, University of Pennsylvania

Energy Constraints on Deformable Models: Recovering Shape and Non-Rigid Motion Demetri Terzopoulos, Andrew Witkin, and Michael Kass, Schlumberger Palo Alto Research

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Kassas and students win four best paper presentation awards

Department of Electrical and Computer Engineering Professor Zak Kassas  and his students received four best paper presentation awards at the Institute of Navigation Global Navigation Satellite Systems Conference ( ION GNSS+ ), held in Denver, Colorado in September.

“It is fulfilling to see our results get recognized by the scientific community,” said Kassas. “ION GNSS+ is the largest annual positioning, navigation, and timing (PNT) conference, and the sessions had papers from highly respected research groups. Aside from these awards, it was particularly rewarding to witness several papers and industrial products at the conference building on our Autonomous Systems Perception, Intelligence, and Navigation ( ASPIN ) Laboratory’s  findings from the past few years.”

Kassas and PhD student Mohammad Neinavaie co-authored a paper titled, “ Joint detection and tracking of unknown beacons for navigation with 5G signals and beyond ”. The paper established the theoretical foundations of novel framework capable of jointly detecting and tracking unknown beacons of terrestrial signals. Experimental results demonstrated the efficacy of the established theory, showing an unmanned aerial vehicle (UAV) and a ground vehicle successfully detecting unknown signals in the environment, from cellular 4G and 5G towers, tracking the signals and navigating the vehicles with these signals.

“ Blind receiver for LEO beacon estimation with application to UAV carrier phase differential navigation ,”co-authored by Kassas and his PhD student Sharbel Kozhaya, proposed an innovative receiver design that can blindly estimate unknown signals transmitted by low Earth orbit (LEO) satellites. Experimental results showed successful blind acquisition and tracking of Orbcomm LEO satellites, which enabled a UAV to navigate with these signals.

 “ Protecting the skies: GNSS-less aircraft navigation with terrestrial cellular signals of opportunity ,” was co-authored by Kassas, his past student and his collaborators from the U.S. Air Force. It showcased revolutionary results from a joint experiment conducted by Kassas’ ASPIN Laboratory and the U.S. Air Force. The results demonstrated the tremendous promise of cellular signals as a reliable back to GPS for high-altitude aircraft navigation. ASPIN’s state-of-the-art cognitive software-defined receivers showed that hundreds of cellular signals can be acquired and tracked at high altitudes, more than 23,000 ft above ground level, and from cellular towers more than 100 km away. The paper also showed meter-level accurate aircraft navigation with only cellular signals over trajectories exceeding 50 km.

 “ Observability analysis of opportunistic receiver localization with LEO satellite pseudorange measurements ,” was co-authored by Kassas and a past student. It analyzed the observability of receiver localization with signals from a single LEO satellite. Experimental results showed a receiver localizing itself with signals from a single Starlink LEO satellite and a single Orbcomm LEO satellite. The results demonstrated the theoretical predictions of the paper’s observability analysis.

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Are best-paper awards for conferences rigged/pre-decided?

Recently I had an acceptance from a very good conference in our field. Three out of four reviewers gave excellent comments, while one gave a poor comment. I was telling my friend that if I had had one more good/excellent review, I could be considered for the best-paper award.

He told me that usually best-paper awards are already fixed and given to the person of the organizer's choice i.e. if the organizers want to invite a distinguished professor, they award their paper etc. etc. So even if I had had an excellent review from the 4th reviewer, there was no chance of getting the award.

What is the backdoor working of best-paper awards - how are they selected?

• 1 Which discipline is this? Not all conferences work like TCS, which is what your example sounds like –  Yemon Choi Commented Jul 23, 2018 at 3:43
• 6 Two comments: (1) I'm not sure any conference of any note rigs the "best paper" award. I can see this happening in conferences hosted by predatory companies, though. (2) Before believe rumours from your friend, I suggest asking him for evidence or doing some investigation yourself. For example, the Thomas Chalmers award given by the Cochrane Collaboration is pretty clear about the eligibility and assessment criteria. Good luck! –  user96258 Commented Jul 23, 2018 at 7:12
• 29 What IS true is that in some (many?) cases the winner(s) of the best paper award are informed that they have won the best paper award before the conference (I imagine for practical reasons, such as ensuring that they will be present when the best paper award is awarded). –  user53923 Commented Jul 23, 2018 at 7:55
• 2 My own experience with the best-poster award was that it was not rigged. I came out of the blue (1st conference, 1st poster), I didn't know anyone and I got a poster award (about 5% of poster presentators earned it). I'm sure this is the same with the best-paper award. But of course it might depend on the conference. –  untreated_paramediensis_karnik Commented Jul 23, 2018 at 19:54
• 3 One more thought about this issue: Maybe the person you were talking to was confusing "best paper" with "invited talk" / "plenary talk" - you were descriping exactly the process how those talks are selected. –  OBu Commented Jul 24, 2018 at 12:00

6 Answers 6

It depends. I received best paper and other awards and have been (slightly) involved also in such a selection process. In each case, I have been to the conference for my first time, was not invited, and I am not very well known. However, it was possible to achieve awards.

In one conference, the organizers had two or three papers on their short-list. The final decision fell depending on the quality of paper presentation. That is absolutely OK in my opinion, I even prefer such an approach as I have seen good papers with really bad presentations getting awards.

At some other conference, I got some special award. At the end of the day, one of the committee members told me he had suggested me because he liked my paper. I did not know him before, thus, this was also not rigged.

When I was a session chair on my own, I was allowed to suggest papers for the best paper award. I had a look at the papers and afterwards at their presentations. I dropped some of them due to their bad presentation and finally recommended one or two (however, they were not awarded, I was just allowed to give my/one opinion).

However, I have seen quite the opposite, unfortunately. In one (not very well known) conference, a guy I met there told me that Ms. X will get some award AGAIN. This happens every year because an award makes it easier for her to get funding for next year. Obviously, she was well known there. And to my surprise, she indeed got awarded. Not a best-paper award, but still some nice certificate.

As far as I have seen, there are huge differences between conferences. I have never seen such bad behavior in highly-reputed ones. If something like that becomes public, they would lose a lot of reputation. Especially since this could mean, that also their peer-review is rigged.

• "In one (not very well known) conference, a guy I met there told me that Ms. X will get some award AGAIN. This happens every year because an award makes it easier for her to get funding for next year" - was this guy an insider in the award committee? Or is it possible that Ms. X just has a record of submitting good papers, and somebody has sour grapes? –  G_B Commented Jul 25, 2018 at 6:56
• @GeoffreyBrent Sometimes, to encourage a better-known individual to attend the conference/event and raise the prestige of the conference/event, they are told "if you attend, we will give you a special award for Y ". This is typically (and I have certainly never seen it not be) a separate award to things like "best paper" - think of it as similar to "Lifetime Achievement Awards" or "Acadamy Honorary Awards" at the Oscars. So, it may be a case of "We know Ms. X only attends because she gets the 'Ms. X is famous' award every year" –  Chronocidal Commented Jul 25, 2018 at 13:41
• @Chronocidal yeah, I can believe that, but it sounds like a separate class of thing from what the OP was asking about, or what J-Kun seemed to be implying. –  G_B Commented Jul 25, 2018 at 23:59

I would find it very unusual and very disturbing if that happened.

In my experience (Computer Science and related fields), conference committees work hard with submissions to select the best paper. And they debate it, as different committee members will typically "champion" a paper that they think is worthy. Often this happens because the committee member is a specialist and recognizes that some paper makes a really significant contribution to some aspect within their speciality.

But I've never seen anything such as you suggest, nor any personal favoritism.

If this sort of thing really exists within a field, I think that it would be a good idea to raise the idea as an ethical issue with that community generally.

• 3 It happens a lot in fact. The weight of the conferences in CS is not shared across fields. Sometimes someone gets an award for more political reasons than research ones. I have seen it happen, specially with more minor awards, such as best poster or best presentation (not best research, but presentation skills). –  Ander Biguri Commented Jul 24, 2018 at 10:06

No. Conference best papers awards are not rigged. Often, associate or track chairs will make decisions based largely (but not entirely) on ratings from peer review. Sometimes, there are awards committees who may take recommendations from reviewers or chairs and make their own decisions. In conferences I've been involved in, awards have always gone to papers among those with the highest average scores.

Because paper quality can never been measured objectively, these decisions are subjective. The reflect the opinions of the award committee or chairs/organizers, and peer reviewers as to what the "best" work is. The process is no more rigged (and no less, I suppose) than the peer review process itself which is also inherently subjective.

There might be some very low status conferences where things are truly rigged but I'm sure these are rare and unlikely to be places you should be submitting anyway.

As someone who has organized award sessions and served on technical programming committee work across multiple disciplines, I would suggest that any conference that might consider such behavior as you describe would be one to avoid. If the organizers repeatedly use awards to entice speakers to the conference, that should be pretty clear from comparing speaker lists and prize lists, which are usually announced. So any sort of systematic bias should be a tip-off.

It is in the own interest of a good conference to select the best papers (according to some suitable, but ultimately subjective, criteria) for the best paper awards. The name of the awards is tied to the conference and if consistently good - in the sense of interesting, original, technically competent, or durable results - papers are selected, this improves the reputation of the conference. If the record is "iffy" or clearly rigged, the conference itself loses aplomb.

James Gleick in his book about Feynman makes this point that the Nobel Prize came to its reputation in particular because in its early phase it had the luck to be awarded to exceedingly important work. This, in turn, improved its own reputation.

Awards are always a two-way road and where not treated as such, there's not much point hoping for them, anyway.

None of the times I've seen a best paper awarded (in a different area to yours) have I considered the selection rigged , nor have I ever heard of a case where it was.

[I have, however, wondered in two cases about competence -- where the supposed 'best' paper had obvious errors - and in one case quite egregious ones - they'd have been shocking even if the paper had been hastily written just the previous evening by an undergraduate. I could say nothing, of course because my own papers had been in the running both times, and it would look like little more than sour grapes to bring them up after that selection. I'd have been quite happy if any number of other papers had won the prize, though. Even many years later I am left to wonder if anyone on the respective committees ever came to realize just how terrible the papers they thought 'best' actually were. It didn't say much for their standards!]

Even in the best circumstances, there can be the common sorts of cognitive biases, of course. Getting a well-known name added to your paper as a co-author can improve the selection committees view of it (especially if a few of them don't really understand it), but that's a different thing from being rigged or pre-decided.

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EDWARD KNIGHTLY

For contributions in design, implementation, and experimental demonstrations of wireless networks

Edward Knightly has made multiple pioneering contributions to wireless networking and is known for bringing research innovations all the way to in-the-field demonstrations.  In 2003, Edward founded the Technology For All Wireless project as a way to bring advanced wireless technology to underserved and under resourced communities. The project yielded award-winning designs and measurement studies, used diverse and shared spectrum spanning an order of magnitude in frequency, impacted Wi-Fi standards, was featured in President Obama’s 2016 Advanced Wireless Research Initiative announcement, and today still serves thousands of Houston’s poorest residents. His contributions to multi-user networking including demonstrating the first multi-user MIMO WLAN, a capability that is now standardized in Wi-Fi since Wi-Fi 5, and more recently, the first uplink multi-user 60 GHz WLAN. He received the Dynamic Spectrum Alliance Award for Research on New Opportunities for Dynamic Spectrum Access. He won eight best paper awards and has given over thirty plenary keynote presentations, both including IEEE INFOCOM.

An IEEE Fellow, Knightly is the Sheafor–Lindsay Professor of Electrical and Computer Engineering at Rice University, Houston, Texas, USA.

2023 INFOCOM Test of Time Paper Awards

The IEEE INFOCOM Test of Time Paper Award recognizes papers published between 10 to 12 years ago (a three-year window) in the INFOCOM proceedings that have been most cited and widely recognized to have a significant impact on the research community.  For 2023, papers published in 2011–2013 INFOCOM proceedings are eligible.

For 2023, the award committee has selected the following papers for this award:

Yi Shi, Liguang Xie, Y. Thomas Hou, Hanif D. Sherali, “ On renewable sensor networks with wireless energy transfer " in Proc. of IEEE INFOCOM 2011 .

Minghong Lin, Adam Wierman, Lachlan L. H. Andrew, Eno Thereska, “ Dynamic right-sizing for power-proportional data centers ” in Proc. of IEEE INFOCOM 2011 .

2023 IEEE INFOCOM Best Paper Awards

Fei Wang, Ethan Hugh and Baochun Li (University of Toronto, Canada) More than Enough is Too Much: Adaptive Defenses against Gradient Leakage in Production Federated Learning

Robert MacDavid, Xiaoqi Chen and Jennifer Rexford (Princeton University, USA) Scalable Real-Time Bandwidth Fairness in Switches

2023 IEEE INFOCOM Best Demo Award

Zhanchen Dong, Jiangong Chen, and Bin Li (The Pennsylvania State University, USA) Collaborative Mixed-Reality-Based Firefighter Training

2023 IEEE INFOCOM Best Poster Award

Yuxia Zhan and Yan Meng (Shanghai Jiao Tong University, China); Lu Zhou (Xidian University, China); Haojin Zhu (Shanghai Jiao Tong University, China) Vetting Privacy Policies in VR: A Data Minimization Principle Perspective

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CVPR 2023 Best Paper Award Winners Announced

Tcpami award recipients recognized.

VANCOUVER, 21 June 2023 – Today, the 2023 Computer Vision and Pattern Recognition (CVPR) Conference Awards Committee announced the winners of its prestigious Best Paper Awards, which annually recognize top research in computer vision, artificial intelligence (AI), machine learning (ML), augmented and virtual reality (AR/VR), deep learning, and much more.

This year, from more than 9,000 paper submissions, the CVPR 2023 Awards Committee selected 12 candidates for the honor of Best Paper, and named the following as this year’s winners:

• Best Paper: Visual Programming: Compositional visual reasoning without training Authors: Tanmay Gupta, Aniruddha Kembhavi ( Author Q&A )
• Best Paper: Planning-oriented Autonomous Driving Authors:  Yihan Hu, Jiazhi Yang, Li Chen, Keyu Li, Chonghao Sima, Xizhou Zhu, Siqi Chai, Senyao Du, Tianwei Lin, Wenhai Wang, Lewei Lu, Xiaosong Jia, Qiang Liu, Jifeng Dai, Yu Qiao, Hongyang Li  ( Author Q&A )
• Best Paper Honorable Mention: DynIBaR: Neural Dynamic Image-Based Rendering Authors: Zhengqi Li, Qianqian Wang, Forrester Cole, Richard Tucker, Noah Snavely
• Best Student Paper: 3D Registration with Maximal Cliques Authors: Xiyu Zhang, Jiaqi Yang, Shikun Zhang, Yanning Zhang
• Best Student Paper Honorable Mention: DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation Authors: Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, Kfir Aberman

“To realize that these recipients were selected from more than 9,000 potential candidates makes them all the more impactful,” said IEEE Computer Society (CS) President Nita Patel, co-sponsor of CVPR 2023. “Clearly, these awards recognize and honor the groundbreaking work being done in the field of computer vision and pattern recognition, and it’s the developments showcased in research like this that will continue to advance and transform our industry.”

“ We congratulate the 2023 award winners as well as everyone who was considered for this year's prizes ,” said Ramin Zabih, founder and president, Computer Vision Foundation (CVF), co-sponsor of CVPR 2023. “ These awards reflect one of the highest achievements in the field of computer vision. Apart from their clear importance on an individual and organizational level, they also serve the global community by recognizing the best of what computer vision currently has to offer and providing an indication of the exciting advances the future holds. ”

Additionally, IEEE CS announced the Technical Community on Pattern Analysis and Machine Intelligence (TCPAMI) Awards at this year’s conference. The following were recognized for their achievements:

• 2023 Recipient: Online Object Tracking: A Benchmark ,  Authors: Yi Wu, Jongwoo Lim, Ming-Hsuan Yang
• 2023 Recipients: Christoph Feichtenhofer and Judy Hoffman
• 2023 Recipient: Alyosha Efros

“These awards demonstrate the longevity and impact of CVPR research,” shared Patel. “We are proud to recognize these achievements and the continued advancements of the computer vision community.”

About CVPR 2023

The Computer Vision and Pattern Recognition Conference (CVPR) is the preeminent computer vision event for new research in support of artificial intelligence (AI), machine learning (ML), augmented and virtual reality (AR/VR), deep learning, and much more. Sponsored by the IEEE Computer Society (CS) and the Computer Vision Foundation (CVF), CVPR delivers the important advances in all areas of computer vision and pattern recognition and the various fields and industries they impact. With first-in-class technical content, a main program, tutorials, workshops, a leading-edge expo, and attended by more than 10,000 people annually, CVPR creates a one-of-a-kind opportunity for networking, recruiting, inspiration, and motivation.

CVPR 2023 is taking place now through 22 June at the Vancouver Convention Center in Vancouver, Canda, and virtually. For more information about CVPR 2023, the program, and how to participate, visit https://cvpr2023.thecvf.com/ .

About the Computer Vision Foundation

The Computer Vision Foundation is a non-profit organization whose purpose is to foster and support research on all aspects of computer vision. Together with the IEEE Computer Society, it co-sponsors the two largest computer vision conferences, CVPR and the International Conference on Computer Vision (ICCV). Visit https://www.thecvf.com/ for more information.

About the IEEE Computer Society

Engaging computer engineers, scientists, academia, and industry professionals from all areas of computing, the IEEE Computer Society (CS) sets the standard for the education and engagement that fuels continued global technological advancement. Through conferences, publications, and programs, and by bringing together computer science and engineering leaders at every phase of their career for dialogue, debate, and collaboration, IEEE CS empowers, shapes, and guides the future of not only its members, but the greater industry, enabling new opportunities to better serve our world. Visit computer.org for more information. 

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Best Paper Award for ACM Periodicals

Reviewed on April 2018

ACM Publications Board Guidelines for Establishing a Best Paper Award for ACM Periodicals

Introduction Many research communities wish to recognize the outstanding work that is being published in their respective areas. One method of recognizing outstanding work published in a journal is to establish a regular Best Paper Award. ACM’s general policies and guidelines for establishing an ACM award can be found at: http://awards.acm.org/ . This document is an adjunct to that document and is intended to provide guidance and policies that are specific to the establishment of a best paper award for an ACM periodical (i.e., journals, transactions, and magazines).

Best Paper Award Proposals The ACM Awards Committee gives pro forma approval to best paper awards, provided they: a) have a written selection process, b) are administered by the appropriate technical committee, c) are not a “Named Award,” and d) include honoraria not exceeding $1,000.00. However, to ensure consistency across the flagship publications of ACM, all best journal/transactions paper awards require approval by the ACM Publications Board. Conference best paper awards are managed by the SIG Governing Board and do not require approval of the Publications Board. Following ACM’s guidelines, a proposal to establish a best paper award must include the following items.

Statement of the award name, purpose of award, and criteria.

A description of the process of obtaining nominations.

A description of the selection process including criteria for selection.

The form of the award (i.e., certificate, plaque, memento, etc.) If the award includes a cash prize, the proposal should include a plan for securing the award’s financial viability.

A statement concerning the frequency of the award.

A statement describing how the chair of the selection committee will be designated and how the selection committee is constituted.

Proposals for journal best paper awards should be submitted to the Director of Publications for consideration by the ACM Publications Board. The following sections provide some additional advice and guidance specific to ACM Best Journal Paper Awards. Award Name For consistency and name recognition, ACM best journal or transaction awards should be named as “Publication_Name Award_Year Best Paper Award.” For example, “ACM Transactions on Computer Systems 2009 Best Paper Award” or “ACM Journal on Computing and Cultural Heritage 2008 Best Paper Award.” It may be appropriate to use the acronym of the transaction or journal in place of the full name of the publication (e.g., “ACM TOPLAS 2004 Best Paper Award.”) In some cases, the sponsoring unit may wish to have the award named in honor of a person or persons. In ACM terminology, this type of award is called a “Named Award.” As described in ACM’s policies on awards, “ACM named awards, including prizes and grants, convey special distinction and require additional justification for approval. Both the merit of the award in the ACM context and the appropriateness of the proposed name will be scrutinized carefully.” The ACM Publications Board, ACM Awards Committee, and ACM Council must approve all Named Best Paper Awards associated with ACM journals. For named best paper and journal awards, the preferred award name would be constructed by including the name of the honored person after the name of the publication. For example, the “ACM TOMM Nicolas D. Georganas Best Paper Award” (see https://tomm.acm.org/honors-awards.cfm ). Award Criteria The proposal should describe the criteria that will be used for selecting the best paper. For best paper awards, technical excellence is typically the most important criteria. However, other criteria such as innovation, significance to the research community, impact, and clarity of presentation can be considered. The award criteria should specify the interval of publication for eligible papers. Some examples are:

All papers published in the previous calendar year.

All papers published in the past two calendar years.

The award for year N considers papers published in calendar year N–10 (i.e., a “test of time” award).

For purposes of determining the publication date of a paper, the date of publication in the ACM Digital Library should be used. Nomination Process The proposal should describe how nominations will be solicited. It is expected that the nomination process allow for anyone to nominate a paper. Self-nominations are permitted. Selection Process Typically an award selection committee will determine the best paper. There should be a designated Chair of the selection committee. The chair is responsible for ensuring the selection process is fair and unbiased and that any possible conflicts of interests are handled appropriately.  The proposal should describe how the chair will be designated and the selection committee is constituted. It should also describe how potential conflicts of interest will be handled. Once the award is established, the rules for the formation of this committee should be documented and publicly available.  It is expected that the selection committee will be made up of recognized experts in the area. The selection committee will often include members of the current Editorial Board.  ACM's Policy on Authorship and Policy on Peer Review  outline the rights and responsibilities of authors and reviewers. In particular, reviewers can expect ACM to maintain their anonymity and to tell them who will see their review. Similarly, authors have the right to know if reviews of their paper will be used for purposes other than editorial decisions. Any selection process should respect these reviewer and author expectations. Award Form As specified in ACM’s policies on awards, if the award includes a cash prize, the award should be endowed or there should be a plan for securing the award’s financial viability. An endowment/financial plan ensures that the prize will be available for each awardee. Similarly if the award includes a memento, arrangements should be made to ensure that the memento is available for presentation.  Award Interval It is very important that the schedule for nominations and selection is published and the schedule maintained. Failure to make an award in a particular year can reflect poorly on those papers published in the period under consideration. 

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2024 IEEE International Conference on Power and Energy (PECon)

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About the Award

Description: The award is conferred upon the author(s) of a paper presented at the 2024 IEEE International Conference on Power and Energy (PECon). The selection of the best papers was made based on the highest scores awarded during the review process, with each paper being evaluated by reviewers specific to its track.

Prize: All winners will be awarded prizes consisting of a certificate and a plaque.

Eligibility: There are no restrictions based on organization, nationality, race, creed, gender, or age, with the sole exceptions being the acceptance of a paper and its presentation at the IEEE PECon 2024. Additionally, IEEE membership is not a prerequisite.

Basis for Judging: The award is presented to the author(s) of a paper showcased at IEEE PECon 2024 that significantly contributes to the advancement of theory and practice in electrical and electronic engineering. This encompasses the development, design, manufacture, and application of electrical systems, apparatus, devices, and controls across industry and commerce. It also includes efforts towards promoting safe, reliable, and economical installations; leadership in energy conservation; addressing environmental, health, and safety concerns; the formulation of voluntary engineering standards and recommended practices; and the professional growth of its members. Finalists are chosen from all accepted papers by the Conference Awards Committee.

Presentation: The winners will be announced at the Best Paper Award Ceremony, with the awards being presented throughout the conference. Should there be no qualified candidates identified, no awards will be distributed.

The last extended date of Registration is 10th August, 2024.

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International conference on mathematics and its applications in science and technology.

(ICMAST - 2024)Hybrid Mode

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5th April, 2024

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20th May, 2024

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30th June, 2024

10th July, 2024

20th July, 2024

Registration deadline

30th July, 2024

10th August, 2024

Paper Acceptance For Presentation Deadline

The main objective of this conference is to provide a forum for researchers, academicians, leading scientists and industries to interact with each other, to exchange new ideas, to discuss challenging issues and explore possibilities for future collaborative works to the general theme of mathematics and its applications in science and engineering. The deliberations at the conference are expected to influence the current researchers regarding their pursuits.

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“Best Paper Presentation Award” ICMAST -2024

The Best Paper Presentation Award aims to recognize and celebrate outstanding contributions to the field of knowledge dissemination through compelling and effective presentations. This accolade is designed to encourage researchers, scholars, and professionals to communicate their work with clarity, impact, and innovation.

• Conference Participation: Candidates must be registered participants in the conference where the paper presentation occurs.
• Content Relevance: The presentation must align with the conference theme and contribute significantly to the relevant field of study.
• Novelty: The content of the presentation should demonstrate originality, novelty, and a valuable contribution to the existing body of knowledge.
• Professionalism: Presenters should adhere to professional conduct, displaying respect for fellow participants, and engaging in constructive discussions.

Papers will be judged on following Criteria:-

The Best Paper Presentation Award seeks to honor not only the depth of research but also the art of effective communication, encouraging presenters to elevate the overall conference experience.

All the winners of best paper presentation will be presented with their awards (certificates) during the awarding ceremony which will be held in-person/online on the last day of the conference along with the conference conclusion.

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Best Paper Presentation Award

Category name: nature study, foundation year of award: 2000, award features: cash prize rs. 1000certificate, award periodicity: annual, award recipient category: individual(m/f), objective: to recognise the best paper published in the journal of isrs during the, international:(country/ brain gain): national.