World's Best Scientists 2026 revealed!
Richard P. Wildes

Richard P. Wildes

D-Index & Metrics

Computer Science

D-Index
38
Citations
11712
World Ranking
9972
National Ranking
398

Richard P. Wildes 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 Richard P. Wildes 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: 110 publications — 11th percentile

11% of scientists in this discipline score the same or lower.

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

Richard P. Wildes 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 Richard P. Wildes 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: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Overview

Richard P. Wildes is a researcher affiliated with York University in Canada. Their work primarily lies in the field of Computer Science, with a strong focus on the subfields of Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience, Signal Processing, and Media Technology.

The scientist's research covers several main topics including Human Pose and Action Recognition, Anomaly Detection Techniques and Applications, Multimodal Machine Learning Applications, Video Surveillance and Tracking Methods, Video Analysis and Summarization, Advanced Vision and Imaging, and Neural Dynamics and Brain Function.

Frequent publication venues for Richard P. Wildes include:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Cerebral Cortex Communications

Some recent representative papers by Richard P. Wildes include:

  • "Where are you heading? Dynamic Trajectory Prediction with Expert Goal Examples" (2021) presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "P3IV: Probabilistic Procedure Planning from Instructional Videos with Weak Supervision" (2022) published in the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying Static vs. Dynamic Information" (2022) in the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Interpretable Deep Feature Propagation for Early Action Recognition" (2021) available on arXiv (Cornell University)
  • "Integration of allocentric and egocentric visual information in a convolutional/multilayer perceptron network model of goal-directed gaze shifts" (2022) published in Cerebral Cortex Communications

Richard P. Wildes has collaborated extensively with several co-authors, including:

  • Konstantinos G. Derpanis
  • Mennatullah Siam
  • He Zhao
  • Matthew Kowal

Their research is marked by a multidisciplinary approach, bridging cognitive neuroscience and various aspects of computer vision and machine learning. This interdisciplinary perspective is reflected in both the range of studied topics and the diversity of publication venues. The focus on dynamic vision tasks such as trajectory prediction and action recognition is evident in the recent works authored or co-authored by them.

Best Publications

  • Iris recognition: an emerging biometric technology

    R.P. Wildes

  • Spatiotemporal Multiplier Networks for Video Action Recognition

    Christoph Feichtenhofer;Axel Pinz;Richard P. Wildes

  • Automated, non-invasive iris recognition system and method

    Richard Patrick Wildes;Jane Circle Asmuth;Keith James Hanna;Stephen Charles Hsu

  • Spatiotemporal Residual Networks for Video Action Recognition

    Christoph Feichtenhofer;Axel Pinz;Richard P. Wildes

  • A machine-vision system for iris recognition

    Richard P. Wildes;Jane C. Asmuth;Gilbert L. Green;Steven C. Hsu

  • A system for automated iris recognition

    R.P. Wildes;J.C. Asmuth;G.L. Green;S.C. Hsu

  • Method and apparatus for performing geo-spatial registration of imagery

    Rakesh Kumar;Stephen Charles Hsu;Keith Hanna;Supun Samarasekera

  • Detecting binocular half-occlusions: empirical comparisons of five approaches

    G. Egnal;R.P. Wildes

  • Aerial video surveillance and exploitation

    R. Kumar;H. Sawhney;S. Samarasekera;S. Hsu

  • Reliable and fast eye finding in close-up images

    T.A. Camus;R. Wildes

  • Iris recognition at a distance

    Craig Fancourt;Luca Bogoni;Keith Hanna;Yanlin Guo

  • Dynamic scene understanding: The role of orientation features in space and time in scene classification

    Konstantinos G. Derpanis;Matthieu Lecce;Kostas Daniilidis;Richard P. Wildes

  • Efficient action spotting based on a spacetime oriented structure representation

    Konstantinos G. Derpanis;Mikhail Sizintsev;Kevin Cannons;Richard P. Wildes

  • Anomalous behaviour detection using spatiotemporal oriented energies, subset inclusion histogram comparison and event-driven processing

    Andrei Zaharescu;Richard Wildes

  • Qualitative Spatiotemporal Analysis Using an Oriented Energy Representation

    Richard P. Wildes;James R. Bergen

  • What Do We Understand About Convolutional Networks

    Isma Hadji;Richard P. Wildes

  • Direct recovery of three-dimensional scene geometry from binocular stereo disparity

    R.P. Wildes

  • Recovering Estimates of Fluid Flow from Image Sequence Data

    Richard P. Wildes;Michael J. Amabile;Ann-Marie Lanzillotto;Tzong-Shyng Leu

  • Spacetime Texture Representation and Recognition Based on a Spatiotemporal Orientation Analysis

    K. G. P. Derpanis;R. Wildes

  • A stereo confidence metric using single view imagery with comparison to five alternative approaches

    Geoffrey Egnal;Max Mintz;Richard P. Wildes

Frequent Co-Authors

Christoph Feichtenhofer
Christoph Feichtenhofer Meta Platforms, Inc.
Axel Pinz
Axel Pinz Graz University of Technology
John K. Tsotsos
John K. Tsotsos York University
Supun Samarasekera
Supun Samarasekera SRI International
Rakesh Kumar
Rakesh Kumar SRI International
Andrew Zisserman
Andrew Zisserman University of Oxford
Harpreet Sawhney
Harpreet Sawhney Microsoft (United States)
Julio C. Martinez-Trujillo
Julio C. Martinez-Trujillo University of Western Ontario
Gene Cheung
Gene Cheung York University
Chia-Wen Lin
Chia-Wen Lin National Tsing Hua University

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