World's Best Scientists 2026 revealed!
Peter V. Gehler

Peter V. Gehler

D-Index & Metrics

Computer Science

D-Index
47
Citations
15564
World Ranking
6316
National Ranking
293

Peter V. Gehler 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 Peter V. Gehler 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: 92 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Peter V. Gehler 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 Peter V. Gehler 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Peter V. Gehler is affiliated with Zalando SE in Germany and primarily publishes in the field of computer science, with a focus on artificial intelligence and computer vision. Their research spans several subfields including domain adaptation, anomaly detection, multimodal machine learning, and generative adversarial networks. The scientist's body of work reflects a strong engagement with machine learning techniques and applications, as well as cancer research and radiological imaging.

Recent papers authored or coauthored by Peter V. Gehler include:

  • "Towards Total Recall in Industrial Anomaly Detection," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations," 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • "Assaying Out-Of-Distribution Generalization in Transfer Learning," 2022, arXiv (Cornell University)
  • "TeST: Test-time Self-Training under Distribution Shift," 2023, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • "Towards causal generative scene models via competition of experts," 2020, arXiv (Cornell University)

The researcher collaborates frequently with several notable coauthors including:

  • Bernhard Schölkopf
  • Francesco Locatello
  • Julius von Kügelgen
  • Matthias Bethge
  • Thomas Brox

Peter V. Gehler's work has been published predominantly in these venues:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

The main topics covered in their publications include:

  • Domain Adaptation and Few-Shot Learning
  • Anomaly Detection Techniques and Applications
  • Multimodal Machine Learning Applications
  • Generative Adversarial Networks and Image Synthesis
  • Cancer-related molecular mechanisms research
  • Machine Learning and Data Classification
  • Adversarial Robustness in Machine Learning

Best Publications

  • 2D Human Pose Estimation: New Benchmark and State of the Art Analysis

    Mykhaylo Andriluka;Leonid Pishchulin;Peter Gehler;Bernt Schiele

  • Keep It SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image

    Federica Bogo;Angjoo Kanazawa;Christoph Lassner;Christoph Lassner;Peter V. Gehler;Peter V. Gehler

  • DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation

    Leonid Pishchulin;Eldar Insafutdinov;Siyu Tang;Bjoern Andres

  • Towards Total Recall in Industrial Anomaly Detection

    Karsten Roth;Latha Pemula;Joaquin Zepeda;Bernhard Schölkopf

  • On feature combination for multiclass object classification

    Peter Gehler;Sebastian Nowozin

  • Unite the People: Closing the Loop Between 3D and 2D Human Representations

    Christoph Lassner;Javier Romero;Martin Kiefel;Federica Bogo

  • Bayesian color constancy revisited

    P.V. Gehler;C. Rother;A. Blake;T. Minka

  • Neural Body Fitting: Unifying Deep Learning and Model Based Human Pose and Shape Estimation

    Mohamed Omran;Christoph Lassner;Gerard Pons-Moll;Peter Gehler

  • Kernel methods for remote sensing data analysis

    Gustavo Camps-Valls;Lorenzo Bruzzone

  • Poselet Conditioned Pictorial Structures

    Leonid Pishchulin;Mykhaylo Andriluka;Peter Gehler;Bernt Schiele

  • Teaching 3D geometry to deformable part models

    Bojan Pepik;Michael Stark;Peter Gehler;Bernt Schiele

  • Strong Appearance and Expressive Spatial Models for Human Pose Estimation

    Leonid Pishchulin;Mykhaylo Andriluka;Peter Gehler;Bernt Schiele

  • Video Propagation Networks

    Varun Jampani;Raghudeep Gadde;Peter V. Gehler

  • A Generative Model of People in Clothing

    Christoph Lassner;Gerard Pons-Moll;Peter V. Gehler

  • Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks

    Varun Jampani;Martin Kiefel;Peter V. Gehler

  • Semantic Video CNNs Through Representation Warping

    Raghudeep Gadde;Varun Jampani;Peter V. Gehler

  • Efficient Nonlinear Markov Models for Human Motion

    Andreas M. Lehrmann;Peter V. Gehler;Sebastian Nowozin

  • Occlusion Patterns for Object Class Detection

    Bojan Pepikj;Michael Stark;Peter Gehler;Bernt Schiele

  • The rate adapting poisson model for information retrieval and object recognition

    Peter V. Gehler;Alex D. Holub;Max Welling

  • Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance

    Carsten Rother;Martin Kiefel;Lumin Zhang;Bernhard Schölkopf

Frequent Co-Authors

Sebastian Nowozin
Sebastian Nowozin Microsoft (United States)
Christoph H. Lampert
Christoph H. Lampert Institute of Science and Technology Austria
Bernt Schiele
Bernt Schiele Max Planck Institute for Informatics
Mykhaylo Andriluka
Mykhaylo Andriluka Google (United States)
Carsten Rother
Carsten Rother Heidelberg University
Michael J. Black
Michael J. Black Max Planck Institute for Intelligent Systems
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Gerard Pons-Moll
Gerard Pons-Moll University of Tübingen
Graham D. Finlayson
Graham D. Finlayson University of East Anglia

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