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Computer Science
USA
2026

D-Index & Metrics

Computer Science

D-Index
120
Citations
59208
World Ranking
146
National Ranking
85

Martial Hebert 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 Martial Hebert 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: 519 publications — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Martial Hebert 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 Martial Hebert 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: 120 D-Index — 99th percentile

99% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award

Overview

Martial Hebert is affiliated with Carnegie Mellon University in the United States and has contributed extensively to research in computer science and engineering. Their work spans multiple subfields, primarily focusing on computer vision and pattern recognition, artificial intelligence, aerospace engineering, geology, and computational mechanics.

The scientist's research covers a range of specialized topics, including:

  • Advanced Vision and Imaging
  • Robotics and Sensor-Based Localization
  • Advanced Neural Network Applications
  • 3D Surveying and Cultural Heritage
  • Domain Adaptation and Few-Shot Learning
  • Video Surveillance and Tracking Methods
  • Multimodal Machine Learning Applications

Martial Hebert has published in various venues, with a significant number of papers appearing on arXiv (Cornell University). Other frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • International Journal of Computer Vision
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

Among recent papers authored under their supervision or collaboration are:

  • "Discovering Objects that Can Move" (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Linear RGB-D SLAM for Structured Environments" (2021), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Constrained Model-based Reinforcement Learning with Robust Cross-Entropy Method" (2020), available on arXiv (Cornell University)
  • "MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments" (2020), available on arXiv (Cornell University)
  • "Flexible Techniques for Differentiable Rendering with 3D Gaussians" (2023), available on arXiv (Cornell University)

Frequent collaborators include the following researchers with notable joint publications:

  • Yu-Xiong Wang
  • Zhipeng Bao
  • Pavel Tokmakov
  • Shuhong Zheng
  • Tiancheng Zhi

The scientist's research interests and output reflect a focus on the integration of machine learning with computer vision, robotics, and 3D imaging technologies. Publications often address both theoretical developments and practical applications in structured environments, autonomous agents, and advanced imaging techniques.

Best Publications

  • Using spin images for efficient object recognition in cluttered 3D scenes

    A.E. Johnson;M. Hebert

  • Autonomous driving in urban environments: Boss and the Urban Challenge

    Chris Urmson;Joshua Anhalt;Drew Bagnell;Christopher Baker

  • A spectral technique for correspondence problems using pairwise constraints

    M. Leordeanu;M. Hebert

  • Putting Objects in Perspective

    D. Hoiem;A.A. Efros;M. Hebert

  • Cross-Stitch Networks for Multi-task Learning

    Ishan Misra;Abhinav Shrivastava;Abhinav Gupta;Martial Hebert

  • Vision and navigation for the Carnegie-Mellon Navlab

    C. Thorpe;M.H. Hebert;T. Kanade;S.A. Shafer

  • The representation, recognition, and locating of 3-d objects

    O D Faugeras;M Hebert

  • Toward Objective Evaluation of Image Segmentation Algorithms

    R. Unnikrishnan;C. Pantofaru;M. Hebert

  • Recovering Surface Layout from an Image

    Derek Hoiem;Alexei A. Efros;Martial Hebert

  • Geometric context from a single image

    D. Hoiem;A.A. Efros;M. Hebert

  • Semi-Supervised Self-Training of Object Detection Models

    C. Rosenberg;M. Hebert;H. Schneiderman

  • Automatic photo pop-up

    Derek Hoiem;Alexei A. Efros;Martial Hebert

  • PCN: Point Completion Network

    Wentao Yuan;Tejas Khot;David Held;Christoph Mertz

  • Shuffle and Learn: Unsupervised Learning Using Temporal Order Verification

    Ishan Misra;C. Lawrence Zitnick;Martial Hebert

  • Simultaneous Localization, Mapping and Moving Object Tracking

    Chieh-Chih Wang;Charles Thorpe;Sebastian Thrun;Martial Hebert

  • Activity forecasting

    Kris M. Kitani;Brian D. Ziebart;James Andrew Bagnell;Martial Hebert

  • Low-Shot Learning from Imaginary Data

    Yu-Xiong Wang;Ross Girshick;Martial Hebert;Bharath Hariharan

  • Efficient visual event detection using volumetric features

    Yan Ke;R. Sukthankar;M. Hebert

  • An empirical study of context in object detection

    Santosh K Divvala;Derek Hoiem;James H Hays;Alexei A Efros

  • Discriminative random fields: a discriminative framework for contextual interaction in classification

    Sanjiv Kumar;Hebert

Frequent Co-Authors

J. Andrew Bagnell
J. Andrew Bagnell Carnegie Mellon University
Takeo Kanade
Takeo Kanade Carnegie Mellon University
Jean Ponce
Jean Ponce École Normale Supérieure
Anthony Stentz
Anthony Stentz Carnegie Mellon University
Katsushi Ikeuchi
Katsushi Ikeuchi Microsoft (United States)
Alexei A. Efros
Alexei A. Efros University of California, Berkeley
Abhinav Gupta
Abhinav Gupta Carnegie Mellon University
Rahul Sukthankar
Rahul Sukthankar Google (United States)
Daniel Huber
Daniel Huber University of Geneva
Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA

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