World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
38134
World Ranking
3719
National Ranking
1775

Svetlana Lazebnik 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 Svetlana Lazebnik 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: 116 publications — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Svetlana Lazebnik 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 Svetlana Lazebnik 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: 57 D-Index — 74th percentile

74% 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

  • 2021 - IEEE Fellow For contributions to computer vision
  • 2013 - Fellow of Alfred P. Sloan Foundation

Overview

Svetlana Lazebnik is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research centers on the field of Computer Science, with a primary focus on Computer Vision and Pattern Recognition. Subfields of study include Artificial Intelligence, Computational Mechanics, Social Psychology, and Control and Systems Engineering.

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

  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • Generative Adversarial Networks and Image Synthesis
  • Human Pose and Action Recognition
  • Reinforcement Learning in Robotics
  • Domain Adaptation and Few-Shot Learning
  • 3D Shape Modeling and Analysis

Recent notable papers include:

  • "Contextual Translation Embedding for Visual Relationship Detection and Scene Graph Generation," 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models," 2024, arXiv (Cornell University)
  • "Revisiting Image-Language Networks for Open-Ended Phrase Detection," 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Memory-Efficient Incremental Learning Through Feature Adaptation," 2020, Lecture notes in computer science

Their frequent co-authors include:

  • Unnat Jain
  • Alexander G. Schwing
  • Viraj Shah
  • Aiyu Cui
  • Daniel McKee

Common publication venues are:

  • arXiv (Cornell University)
  • UNC Libraries
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Lecture notes in computer science

Svetlana Lazebnik has been recognized as a Fellow of the Alfred P. Sloan Foundation in 2013. In 2021, they were named an IEEE Fellow for contributions to computer vision.

Best Publications

  • Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories

    S. Lazebnik;C. Schmid;J. Ponce

  • Iterative Quantization: A Procrustean Approach to Learning Binary Codes for Large-Scale Image Retrieval

    Yunchao Gong;Svetlana Lazebnik;Albert Gordo;Florent Perronnin

  • Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study

    Jianguo Zhang;M. Marszalek;S. Lazebnik;C. Schmid

  • A sparse texture representation using local affine regions

    S. Lazebnik;C. Schmid;J. Ponce

  • Iterative quantization: A procrustean approach to learning binary codes

    Yunchao Gong;Svetlana Lazebnik

  • Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models

    Bryan A. Plummer;Liwei Wang;Chris M. Cervantes;Juan C. Caicedo

  • Multi-scale Orderless Pooling of Deep Convolutional Activation Features

    Yunchao Gong;Liwei Wang;Ruiqi Guo;Svetlana Lazebnik

  • PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning

    Arun Mallya;Svetlana Lazebnik

  • Superparsing: Scalable Nonparametric Image Parsing with Superpixels

    Joseph Tighe;Svetlana Lazebnik

  • Learning Deep Structure-Preserving Image-Text Embeddings

    Liwei Wang;Yin Li;Svetlana Lazebnik

  • Locality-sensitive binary codes from shift-invariant kernels

    Maxim Raginsky;Svetlana Lazebnik

  • Building Rome on a cloudless day

    Jan-Michael Frahm;Pierre Fite-Georgel;David Gallup;Tim Johnson

  • Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

    Arun Mallya;Dillon Davis;Svetlana Lazebnik

  • A Multi-View Embedding Space for Modeling Internet Images, Tags, and Their Semantics

    Yunchao Gong;Qifa Ke;Michael Isard;Svetlana Lazebnik

  • 3D Object Modeling and Recognition Using Local Affine-Invariant Image Descriptors and Multi-View Spatial Constraints

    Fred Rothganger;Svetlana Lazebnik;Cordelia Schmid;Jean Ponce

  • Learning Two-Branch Neural Networks for Image-Text Matching Tasks

    Liwei Wang;Yin Li;Jing Huang;Svetlana Lazebnik

  • Scene recognition and weakly supervised object localization with deformable part-based models

    Megha Pandey;Svetlana Lazebnik

  • Active Object Localization with Deep Reinforcement Learning

    Juan C. Caicedo;Svetlana Lazebnik

  • Where to Buy It: Matching Street Clothing Photos in Online Shops

    M. Hadi Kiapour;Xufeng Han;Svetlana Lazebnik;Alexander C. Berg

  • Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs

    Xiaowei Li;Changchang Wu;Christopher Zach;Svetlana Lazebnik

  • Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models

    Bryan A. Plummer;Liwei Wang;Chris M. Cervantes;Juan C. Caicedo

  • Local Features and Kernels for Classication of Texture and Object Categories: A Comprehensive Study

    Jianguo Zhang;Svetlana Lazebnik;Cordelia Schmid

Frequent Co-Authors

Jean Ponce
Jean Ponce École Normale Supérieure
Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA
Alexander G. Schwing
Alexander G. Schwing University of Illinois at Urbana-Champaign
Liwei Wang
Liwei Wang Peking University
Yoichi Sato
Yoichi Sato University of Tokyo
Pietro Perona
Pietro Perona California Institute of Technology
Ali Farhadi
Ali Farhadi University of Washington
Julia Hockenmaier
Julia Hockenmaier University of Illinois at Urbana-Champaign
Tamara L. Berg
Tamara L. Berg University of North Carolina at Chapel Hill

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