World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
77
Citations
51541
World Ranking
1230
National Ranking
650

Jamie Shotton 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 Jamie Shotton 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: 177 publications — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Jamie Shotton 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 Jamie Shotton 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: 77 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Overview

Jamie Shotton is affiliated with Microsoft in the United States. Their research primarily spans the fields of computer science and engineering, with a focus on specialized areas including computer vision and pattern recognition, artificial intelligence, computational mechanics, control and systems engineering, and signal processing.

Their work covers a range of topics that include:

  • Face recognition and analysis
  • Multimodal machine learning applications
  • Generative adversarial networks and image synthesis
  • 3D shape modeling and analysis
  • Human pose and action recognition
  • Human motion and animation
  • Advanced image and video retrieval techniques

Jamie Shotton has published extensively, with many contributions appearing in prominent venues. Frequent publication sources include:

  • arXiv (Cornell University)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Lecture Notes in Computer Science

Representative papers showcase Shotton's contributions to computer vision and related fields. Selected recent papers include:

  • Full-Body Motion from a Single Head-Mounted Device: Generating SMPL Poses from Partial Observations, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • FastNeRF: High-Fidelity Neural Rendering at 200FPS, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Model-Based Imitation Learning for Urban Driving, 2022, arXiv (Cornell University)
  • GAIA-1: A Generative World Model for Autonomous Driving, 2023, arXiv (Cornell University)
  • CONFIG: Controllable Neural Face Image Generation, 2020, Lecture Notes in Computer Science

The scientist has collaborated frequently with several researchers, including:

  • M. Kowalski
  • Matthew Johnson
  • Alex Kendall
  • Thomas J. Cashman
  • Sebastian Dziadzio

Best Publications

  • Real-time human pose recognition in parts from single depth images

    Jamie Shotton;Andrew Fitzgibbon;Mat Cook;Toby Sharp

  • The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

    Bjoern H. Menze;Andras Jakab;Stefan Bauer;Jayashree Kalpathy-Cramer

  • KinectFusion: Real-time dense surface mapping and tracking

    Richard A. Newcombe;Shahram Izadi;Otmar Hilliges;David Molyneaux

  • Real-time human pose recognition in parts from single depth images

    Jamie Shotton;Toby Sharp;Alex Kipman;Andrew Fitzgibbon

  • KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera

    Shahram Izadi;David Kim;Otmar Hilliges;David Molyneaux

  • Enhanced Computer Vision With Microsoft Kinect Sensor: A Review

    Jungong Han;Ling Shao;Dong Xu;Jamie Shotton

  • TextonBoost : joint appearance, shape and context modeling for multi-class object recognition and segmentation

    Jamie Shotton;John Winn;Carsten Rother;Antonio Criminisi

  • Semantic texton forests for image categorization and segmentation

    J. Shotton;M. Johnson;R. Cipolla

  • TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context

    Jamie Shotton;John Winn;Carsten Rother;Antonio Criminisi

  • Segmentation and Recognition Using Structure from Motion Point Clouds

    Gabriel J. Brostow;Jamie Shotton;Julien Fauqueur;Roberto Cipolla

  • Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold, Learning and Semi-supervised Learning

    Antonio Criminisi;Jamie Shotton;Ender Konukoglu

  • Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images

    Jamie Shotton;Ben Glocker;Christopher Zach;Shahram Izadi

  • Decision Forests for Computer Vision and Medical Image Analysis

    A. Criminisi;J. Shotton

  • Learning 6D Object Pose Estimation Using 3D Object Coordinates

    Eric Brachmann;Alexander Krull;Frank Michel;Stefan Gumhold

  • Multiscale Categorical Object Recognition Using Contour Fragments

    J. Shotton;A. Blake;R. Cipolla

  • Efficient Human Pose Estimation from Single Depth Images

    Jamie Shotton;Ross Girshick;Andrew Fitzgibbon;Toby Sharp

  • DSAC — Differentiable RANSAC for Camera Localization

    Eric Brachmann;Alexander Krull;Sebastian Nowozin;Jamie Shotton

  • Accurate, Robust, and Flexible Real-time Hand Tracking

    Toby Sharp;Cem Keskin;Duncan Robertson;Jonathan Taylor

  • Efficient regression of general-activity human poses from depth images

    Ross Girshick;Jamie Shotton;Pushmeet Kohli;Antonio Criminisi

  • Contour-based learning for object detection

    J. Shotton;A. Blake;R. Cipolla

Frequent Co-Authors

Antonio Criminisi
Antonio Criminisi Microsoft (United States)
Pushmeet Kohli
Pushmeet Kohli DeepMind (United Kingdom)
Shahram Izadi
Shahram Izadi Google (United States)
David Kim
David Kim Microsoft (United States)
Otmar Hilliges
Otmar Hilliges ETH Zurich
John Winn
John Winn Microsoft (United States)
Carsten Rother
Carsten Rother Heidelberg University
Roberto Cipolla
Roberto Cipolla University of Cambridge
Andrew Blake
Andrew Blake University of Cambridge

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