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Computer Science

D-Index
90
Citations
32200
World Ranking
610
National Ranking
326

Overview

James M. Rehg is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research is primarily concentrated in the field of Computer Science with a significant focus on Computer Vision and Pattern Recognition.

The main areas of study for their work include:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Human-Computer Interaction
  • Cognitive Neuroscience
  • Computational Mechanics

The key topics covered in their research are:

  • Human Pose and Action Recognition
  • Multimodal Machine Learning Applications
  • Advanced Vision and Imaging
  • Video Surveillance and Tracking Methods
  • Video Analysis and Summarization
  • 3D Shape Modeling and Analysis
  • Domain Adaptation and Few-Shot Learning

James M. Rehg has contributed extensively to several publication venues. Frequent venues include:

  • arXiv (Cornell University)
  • Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2021 International Conference on 3D Vision (3DV)
  • International Journal of Computer Vision

The scientist has a range of recent papers, notable for their contribution to egocentric video analysis, gaze estimation, and 3D vision:

  • "Ego4D: Around the World in 3,000 Hours of Egocentric Video," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "In the Eye of the Beholder: Gaze and Actions in First Person Video," 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Detection of eye contact with deep neural networks is as accurate as human experts," 2020, Nature Communications
  • "4D Human Body Capture from Egocentric Video via 3D Scene Grounding," 2021, 2021 International Conference on 3D Vision (3DV)
  • "In the Eye of Transformer: Global-Local Correlation for Egocentric Gaze Estimation and Beyond," 2023, International Journal of Computer Vision

Collaboration is evident in their frequent co-authors, which include:

  • Miao Liu
  • Fiona Ryan
  • Anh Thai
  • Bolin Lai
  • Stefan Stojanov

Best Publications

  • Statistical color models with application to skin detection

    M.J. Jones;J.M. Rehg

  • The Secrets of Salient Object Segmentation

    Yin Li;Xiaodi Hou;Christof Koch;James M. Rehg

  • CENTRIST: A Visual Descriptor for Scene Categorization

    Jianxin Wu;J M Rehg

  • Multiple Hypothesis Tracking Revisited

    Chanho Kim;Fuxin Li;Arridhana Ciptadi;James M. Rehg

  • Visual tracking of high DOF articulated structures: an application to human hand tracking

    James M. Rehg;Takeo Kanade

  • Model-based tracking of self-occluding articulated objects

    J.M. Rehg;T. Kanade

  • Video Segmentation by Tracking Many Figure-Ground Segments

    Fuxin Li;Taeyoung Kim;Ahmad Humayun;David Tsai

  • Learning to recognize objects in egocentric activities

    Alireza Fathi;Xiaofeng Ren;James M. Rehg

  • Fine-Grained Head Pose Estimation Without Keypoints

    Nataniel Ruiz;Eunji Chong;James M. Rehg

  • A multiple hypothesis approach to figure tracking

    Tat-Jen Cham;J.M. Rehg

  • Motion Coherent Tracking Using Multi-label MRF Optimization

    David Tsai;Matthew Flagg;Atsushi Nakazawa;James M. Rehg

  • Learning to recognize daily actions using gaze

    Alireza Fathi;Yin Li;James M. Rehg

  • Information theoretic MPC for model-based reinforcement learning

    Grady Williams;Nolan Wagener;Brian Goldfain;Paul Drews

  • Social interactions: A first-person perspective

    Alircza Fathi;Jessica K. Hodgins;James M. Rehg

  • A Scalable Approach to Activity Recognition based on Object Use

    Jianxin Wu;A. Osuntogun;T. Choudhury;M. Philipose

  • Ego4D: Around the World in 3,000 Hours of Egocentric Video

    Kristen Grauman;Andrew Westbury;Eugene Byrne;Zachary Chavis

  • Understanding egocentric activities

    Alireza Fathi;Ali Farhadi;James M. Rehg

  • Learning Switching Linear Models of Human Motion

    Vladimir Pavlovic;James M. Rehg;John MacCormick

  • Aggressive driving with model predictive path integral control

    Grady Williams;Paul Drews;Brian Goldfain;James M. Rehg

  • Fast Asymmetric Learning for Cascade Face Detection

    Jianxin Wu;S.C. Brubaker;M.D. Mullin;J.M. Rehg

  • A dynamic Bayesian network approach to figure tracking using learned dynamic models

    V. Pavlovic;J.M. Rehg;Tat-Jen Cham;K.P. Murphy

Frequent Co-Authors

Yin Li
Yin Li Chinese Academy of Sciences
Vladimir Pavlovic
Vladimir Pavlovic Rutgers, The State University of New Jersey
Tat-Jen Cham
Tat-Jen Cham Nanyang Technological University
Gregory D. Abowd
Gregory D. Abowd Northeastern University
Evangelos A. Theodorou
Evangelos A. Theodorou Georgia Institute of Technology
Umakishore Ramachandran
Umakishore Ramachandran Georgia Institute of Technology
Jianxin Wu
Jianxin Wu Nanjing University
Irfan Essa
Irfan Essa Georgia Institute of Technology
Frank Dellaert
Frank Dellaert Georgia Institute of Technology
Charles C. Kemp
Charles C. Kemp Georgia Institute of Technology

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