World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
75
Citations
35332
World Ranking
1376
National Ranking
25

Lior Wolf 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 Lior Wolf 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: 379 publications — 85th percentile

85% of scientists in this discipline score the same or lower.

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

Lior Wolf 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 Lior Wolf 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: 75 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Overview

Lior Wolf is affiliated with Tel Aviv University in Israel and works primarily in the field of computer science. Their research output spans multiple subfields, with a particular focus on computer vision and pattern recognition, artificial intelligence, and signal processing. Additional work covers areas such as electrical and electronic engineering and radiology, nuclear medicine, and imaging.

The scientist's research topics include:

  • Generative Adversarial Networks and Image Synthesis
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Speech and Audio Processing
  • Explainable Artificial Intelligence (XAI)
  • Neural Networks and Applications

Lior Wolf's recent papers illustrate active contributions to diverse aspects of machine learning and computer vision. Examples include:

  • "Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Models" (2023), published in ACM Transactions on Graphics
  • "DeepFake Detection Based on Discrepancies Between Faces and Their Context" (2021), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "ZeroCap: Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic" (2022), presented at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Data Augmenting Contrastive Learning of Speech Representations in the Time Domain" (2020), available on arXiv (Cornell University)
  • "Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks" (2020), published in Proceedings of the AAAI Conference on Artificial Intelligence

Their publication record shows frequent appearances in specific venues, including:

  • arXiv (Cornell University), with over 130 publications
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • ACM Transactions on Graphics
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Lior Wolf collaborates repeatedly with several coauthors, among whom are Eliya Nachmani, Sagie Benaim, Hila Chefer, Shir Gur, and Tal Shaharabany.

Best Publications

  • DeepFace: Closing the Gap to Human-Level Performance in Face Verification

    Yaniv Taigman;Ming Yang;Marc'Aurelio Ranzato;Lior Wolf

  • Robust Object Recognition with Cortex-Like Mechanisms

    T. Serre;L. Wolf;S. Bileschi;M. Riesenhuber

  • Face recognition in unconstrained videos with matched background similarity

    Lior Wolf;Tal Hassner;Itay Maoz

  • Object recognition with features inspired by visual cortex

    T. Serre;L. Wolf;T. Poggio

  • A Biologically Inspired System for Action Recognition

    H. Jhuang;T. Serre;L. Wolf;T. Poggio

  • Unsupervised Cross-Domain Image Generation

    Yaniv Taigman;Adam Polyak;Lior Wolf

  • Using the Output Embedding to Improve Language Models

    Ofir Press;Lior Wolf

  • Plasmonic nanostructure design and characterization via Deep Learning.

    Itzik Malkiel;Michael Mrejen;Achiya Nagler;Uri Arieli

  • Non-homogeneous Content-driven Video-retargeting

    L. Wolf;M. Guttmann;D. Cohen-Or

  • Descriptor Based Methods in the Wild

    Lior Wolf;Tal Hassner;Yaniv Taigman

  • Transformer Interpretability Beyond Attention Visualization

    Hila Chefer;Shir Gur;Lior Wolf

  • Local Trinary Patterns for human action recognition

    Lahav Yeffet;Lior Wolf

  • Chest pathology detection using deep learning with non-medical training

    Yaniv Bar;Idit Diamant;Lior Wolf;Sivan Lieberman

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

    L. Wolf;T. Hassner;Y. Taigman

  • System, method and a computer readible medium for providing an output image

    Lior Wolf;Moshe Guttman;Daniel Cohen-Or

  • Learning over sets using kernel principal angles

    Lior Wolf;Amnon Shashua

  • Similarity scores based on background samples

    Lior Wolf;Tal Hassner;Yaniv Taigman

  • Deep learning with non-medical training used for chest pathology identification

    Yaniv Bar;Idit Diamant;Lior Wolf;Hayit Greenspan

  • Optimizing Photo Composition

    Ligang Liu;Renjie Chen;Lior Wolf;Daniel Cohen-Or

  • Associating neural word embeddings with deep image representations using Fisher Vectors

    Benjamin Klein;Guy Lev;Gil Sadeh;Lior Wolf

Frequent Co-Authors

Nachum Dershowitz
Nachum Dershowitz Tel Aviv University
Tal Hassner
Tal Hassner Facebook (United States)
Amnon Shashua
Amnon Shashua Hebrew University of Jerusalem
Daniel Cohen-Or
Daniel Cohen-Or Tel Aviv University
Thomas Serre
Thomas Serre Brown University
Hayit Greenspan
Hayit Greenspan Tel Aviv University
Eytan Ruppin
Eytan Ruppin National Institutes of Health
Marc'Aurelio Ranzato
Marc'Aurelio Ranzato DeepMind (United Kingdom)
Dovi Poznanski
Dovi Poznanski Tel Aviv University

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