World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
14905
World Ranking
5235
National Ranking
2409

Tal Hassner 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 Tal Hassner 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: 108 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.

Tal Hassner 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 Tal Hassner 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: 51 D-Index — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Overview

Tal Hassner is affiliated with Facebook in the United States. Their primary research field is Computer Science, with a particular focus on Computer Vision and Pattern Recognition, which accounts for the majority of their publications. Other subfields include Artificial Intelligence, Media Technology, Signal Processing, and Safety Research.

Hassner's research topics encompass a range of areas linked to machine learning and visual data analysis. Notably, these topics include Handwritten Text Recognition Techniques, Digital Media Forensic Detection, Generative Adversarial Networks and Image Synthesis, Adversarial Robustness in Machine Learning, Anomaly Detection Techniques and Applications, Face Recognition and Analysis, as well as Natural Language Processing Techniques.

Recent papers authored or coauthored by Hassner demonstrate a focus on detecting and synthesizing visual content, often with implications for media authenticity and transfer learning. Key publications include:

  • DeepFake Detection Based on Discrepancies Between Faces and Their Context, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • LEEP: A New Measure to Evaluate Transferability of Learned Representations, 2020, arXiv (Cornell University)
  • FSGANv2: Improved Subject Agnostic Face Swapping and Reenactment, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • TextStyleBrush: Transfer of Text Aesthetics From a Single Example, 2023, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Few-shot Learning with Noisy Labels, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Hassner frequently collaborates with several researchers, including Giovanni Maria Farinella, Shai Avidan, Gabriel Brostow, Moustapha Cissé, and Kevin J Liang. The collaborative work with these coauthors has contributed to a wide range of publications.

Publications by Tal Hassner are often featured in prominent venues, including:

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

In addition to journal and conference papers, Hassner has contributed extensively to book publications with Springer Science+Business Media. Notably, Hassner has numerous chapters in titles such as Computer Vision - ECCV 2022 and Image Analysis and Processing - ICIAP 2022, reflecting their continued involvement in advancing comprehensive research dissemination.

Best Publications

  • Face recognition in unconstrained videos with matched background similarity

    Lior Wolf;Tal Hassner;Itay Maoz

  • Age and Gender Estimation of Unfiltered Faces

    Eran Eidinger;Roee Enbar;Tal Hassner

  • Effective face frontalization in unconstrained images

    Tal Hassner;Shai Harel;Eran Paz;Roee Enbar

  • Deep Face Recognition: A Survey

    Iacopo Masi;Yue Wu;Tal Hassner;Prem Natarajan

  • Descriptor Based Methods in the Wild

    Lior Wolf;Tal Hassner;Yaniv Taigman

  • Violent flows: Real-time detection of violent crowd behavior

    Tal Hassner;Yossi Itcher;Orit Kliper-Gross

  • FSGAN: Subject Agnostic Face Swapping and Reenactment

    Yuval Nirkin;Yosi Keller;Tal Hassner

  • Regressing Robust and Discriminative 3D Morphable Models with a Very Deep Neural Network

    Anh Tuan Tran;Tal Hassner;Iacopo Masi;Gerard Medioni

  • Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics

    L. Wolf;T. Hassner;Y. Taigman

  • Do We Really Need to Collect Millions of Faces for Effective Face Recognition

    Iacopo Masi;Anh Tuan Tran;Jatuporn Toy Leksut;Tal Hassner;Tal Hassner

  • Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns

    Gil Levi;Tal Hassner

  • Similarity scores based on background samples

    Lior Wolf;Tal Hassner;Yaniv Taigman

  • On Face Segmentation, Face Swapping, and Face Perception

    Yuval Nirkin;Iacopo Masi;Anh Tran Tuan;Tal Hassner

  • DeepFake Detection Based on Discrepancies Between Faces and their Context.

    Yuval Nirkin;Lior Wolf;Yosi Keller;Tal Hassner

  • Motion interchange patterns for action recognition in unconstrained videos

    Orit Kliper-Gross;Yaron Gurovich;Tal Hassner;Lior Wolf

  • Multiple One-Shots for Utilizing Class Label Information.

    Yaniv Taigman;Lior Wolf;Tal Hassner

  • Facial Landmark Detection with Tweaked Convolutional Neural Networks

    Yue Wu;Tal Hassner;KangGeon Kim;Gerard Medioni

  • Mask TextSpotter v3: Segmentation Proposal Network for Robust Scene Text Spotting

    Minghui Liao;Guan Pang;Jing Huang;Tal Hassner

  • HyperSeg: Patch-wise Hypernetwork for Real-time Semantic Segmentation

    Yuval Nirkin;Lior Wolf;Tal Hassner

  • Face recognition using deep multi-pose representations

    Wael AbdAlmageed;Yue Wu;Stephen Rawls;Shai Harel

  • Precise Detection in Densely Packed Scenes

    Eran Goldman;Roei Herzig;Aviv Eisenschtat;Jacob Goldberger

  • Viewing Real-World Faces in 3D

    Tal Hassner

  • Extreme 3D Face Reconstruction: Seeing Through Occlusions

    Anh Tuan Tran;Tal Hassner;Iacopo Masi;Eran Paz

  • LEEP: A New Measure to Evaluate Transferability of Learned Representations

    Cuong V. Nguyen;Tal Hassner;Matthias Seeger;Cedric Archambeau

Frequent Co-Authors

Gerard Medioni
Gerard Medioni Amazon (United States)
Lior Wolf
Lior Wolf Tel Aviv University
Ronen Basri
Ronen Basri Weizmann Institute of Science
Prem Natarajan
Prem Natarajan Capital One (United States)
Lihi Zelnik-Manor
Lihi Zelnik-Manor Technion – Israel Institute of Technology
Jongmoo Choi
Jongmoo Choi University of Southern California
Jing Huang
Jing Huang Peking University
Nachum Dershowitz
Nachum Dershowitz Tel Aviv University
Shai Avidan
Shai Avidan Tel Aviv University
Yaron Lipman
Yaron Lipman Facebook (United States)

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