World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
90
Citations
32200
World Ranking
610
National Ranking
327

James M. Rehg publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where James M. Rehg sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 335 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

James M. Rehg D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where James M. Rehg sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 90 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

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
Umakishore Ramachandran
Umakishore Ramachandran Georgia Institute of Technology
Evangelos A. Theodorou
Evangelos A. Theodorou Georgia Institute of Technology
Jianxin Wu
Jianxin Wu Nanjing University
Joel S. Schuman
Joel S. Schuman Wills Eye Hospital
Irfan Essa
Irfan Essa Georgia Institute of Technology
Hiroshi Ishikawa
Hiroshi Ishikawa Oregon Health & Science University

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