World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
14613
World Ranking
9492
National Ranking
589

Gabriel J. Brostow 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 Gabriel J. Brostow 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: 97 publications — 8th percentile

8% of scientists in this discipline score the same or lower.

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

Gabriel J. Brostow 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 Gabriel J. Brostow 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Gabriel J. Brostow is affiliated with University College London in the United Kingdom. Their research spans multiple disciplines within computer science and engineering, with significant contributions to computer vision and pattern recognition.

The main fields of study associated with Brostow include:

  • Computer Science
  • Engineering

Brostow's work covers several subfields such as:

  • Computer Vision and Pattern Recognition
  • Aerospace Engineering
  • Artificial Intelligence
  • Media Technology
  • Molecular Biology

The scientist's research topics are diverse, focusing on areas including:

  • Advanced Vision and Imaging
  • Advanced Image and Video Retrieval Techniques
  • Robotics and Sensor-Based Localization
  • Domain Adaptation and Few-Shot Learning
  • Remote-Sensing Image Classification
  • Advanced Neural Network Applications
  • 3D Surveying and Cultural Heritage

Recent notable papers authored by Brostow are:

  • "Shazam for bats: Internet of Things for continuous real-time biodiversity monitoring" (2021), published in IET Smart Cities
  • "Focus on the Positives: Self-Supervised Learning for Biodiversity Monitoring" (2021), presented at the 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "SVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained Models" (2022), available on arXiv (Cornell University)
  • "Image Stylization for Robust Features" (2020), available on arXiv (Cornell University)
  • "LookOut! Interactive Camera Gimbal Controller for Filming Long Takes" (2022), published in ACM Transactions on Graphics

Frequent co-authors collaborating with Brostow include:

  • Shai Avidan
  • Moustapha Cissé
  • Giovanni Maria Farinella
  • Tal Hassner
  • Oisin Mac Aodha

Brostow has published extensively in venues such as:

  • arXiv (Cornell University)
  • Lecture notes in computer science
  • IET Smart Cities
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

The scientist has also contributed books published by Springer Science+Business Media, with a significant number of chapters in "Computer Vision - ECCV 2022".

Best Publications

  • Unsupervised Monocular Depth Estimation with Left-Right Consistency

    Clement Godard;Oisin Mac Aodha;Gabriel J. Brostow

  • Digging Into Self-Supervised Monocular Depth Estimation

    Clement Godard;Oisin Mac Aodha;Michael Firman;Gabriel Brostow

  • Semantic object classes in video: A high-definition ground truth database

    Gabriel J. Brostow;Julien Fauqueur;Roberto Cipolla

  • Segmentation and Recognition Using Structure from Motion Point Clouds

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

  • Harmonic Networks: Deep Translation and Rotation Equivariance

    Daniel E. Worrall;Stephan J. Garbin;Daniyar Turmukhambetov;Gabriel J. Brostow

  • Unsupervised Bayesian Detection of Independent Motion in Crowds

    G.J. Brostow;R. Cipolla

  • Deep blending for free-viewpoint image-based rendering

    Peter Hedman;Julien Philip;True Price;Jan-Michael Frahm

  • The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth

    Jamie Watson;Oisin Mac Aodha;Victor Prisacariu;Gabriel Brostow

  • Automatic Joint Parameter Estimation from Magnetic Motion Capture Data

    James F. O'Brien;Robert E. Bodenheimer;Gabriel Julian Brostow;Jessica K. Hodgins

  • Bat detective—Deep learning tools for bat acoustic signal detection

    Oisin Mac Aodha;Rory Gibb;Kate E. Barlow;Ella Browning;Ella Browning

  • Patch based synthesis for single depth image super-resolution

    Oisin Mac Aodha;Neill D. F. Campbell;Arun Nair;Gabriel J. Brostow

  • Non-rigid Photometric Stereo with Colored Lights

    C. Hernandez;G. Vogiatzis;G.J. Brostow;B. Stenger

  • Self-Supervised Monocular Depth Hints

    Jamie Watson;Michael Firman;Gabriel Brostow;Daniyar Turmukhambetov

  • Structured Prediction of Unobserved Voxels from a Single Depth Image

    Michael Firman;Oisin Mac Aodha;Simon Julier;Gabriel J. Brostow

  • Unstructured video-based rendering: interactive exploration of casually captured videos

    Luca Ballan;Gabriel J. Brostow;Jens Puwein;Marc Pollefeys

  • RAPter: rebuilding man-made scenes with regular arrangements of planes

    Aron Monszpart;Nicolas Mellado;Gabriel J. Brostow;Niloy J. Mitra

  • Hierarchical Subquery Evaluation for Active Learning on a Graph

    Oisin Mac Aodha;Neill D. F. Campbell;Jan Kautz;Gabriel J. Brostow

  • Scalable inside-out image-based rendering

    Peter Hedman;Tobias Ritschel;George Drettakis;Gabriel Brostow

  • Learning to Remove Soft Shadows

    Maciej Gryka;Michael Terry;Gabriel J. Brostow

  • CubeNet: Equivariance to 3D Rotation and Translation

    Daniel E. Worrall;Gabriel J. Brostow

  • Capturing Time-of-Flight data with confidence

    Malcolm Reynolds;Jozef Dobos;Leto Peel;Tim Weyrich

Frequent Co-Authors

Roberto Cipolla
Roberto Cipolla University of Cambridge
Kate E. Jones
Kate E. Jones University College London
Marc Pollefeys
Marc Pollefeys ETH Zurich
Jamie Shotton
Jamie Shotton Microsoft (United States)
Irfan Essa
Irfan Essa Georgia Institute of Technology
Mark Girolami
Mark Girolami University of Cambridge
Daniel C. Alexander
Daniel C. Alexander University College London
Jan Kautz
Jan Kautz Nvidia (United States)
Danail Stoyanov
Danail Stoyanov University College London
George Drettakis
George Drettakis French Institute for Research in Computer Science and Automation - INRIA

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