World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
60
Citations
13135
World Ranking
3268
National Ranking
152

Bodo Rosenhahn 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 Bodo Rosenhahn 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: 401 publications — 87th percentile

87% of scientists in this discipline score the same or lower.

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

Bodo Rosenhahn 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 Bodo Rosenhahn 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: 60 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Overview

Bodo Rosenhahn is affiliated with the University of Hannover in Germany. Their research focuses primarily on computer science and engineering, with significant contributions in the subfields of computer vision and pattern recognition, artificial intelligence, molecular biology, biomedical engineering, and electrical and electronic engineering.

The scientist's recent published papers include:

  • Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection, 2022, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • RelTR: Relation Transformer for Scene Graph Generation, 2023, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Asymmetric Student-Teacher Networks for Industrial Anomaly Detection, 2023, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • Text to Image Generation with Semantic-Spatial Aware GAN, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Spatial-Temporal Transformer for Dynamic Scene Graph Generation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Their frequent co-authors include Michael Ying Yang, Wentong Liao, Marco Rudolph, Frederik Schubert, and Yuren Cong.

Common publication venues for Rosenhahn's work are:

  • arXiv (Cornell University)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Transactions on Games

The main topics covered in Rosenhahn's research include:

  • Anomaly Detection Techniques and Applications
  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition
  • Advanced Neural Network Applications
  • Generative Adversarial Networks and Image Synthesis
  • Video Surveillance and Tracking Methods
  • Advanced Image and Video Retrieval Techniques

Best Publications

  • Recovering Accurate {3D} Human Pose in the Wild Using {IMUs} and a Moving Camera

    Timo von Marcard;Roberto Henschel;Michael J. Black;Bodo Rosenhahn

  • Motion capture using joint skeleton tracking and surface estimation

    Juergen Gall;Carsten Stoll;Edilson de Aguiar;Christian Theobalt

  • A Statistical Model of Human Pose and Body Shape

    Nils Hasler;Carsten Stoll;Martin Sunkel;Bodo Rosenhahn

  • Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows

    Marco Rudolph;Bastian Wandt;Bodo Rosenhahn

  • Automatic human model generation

    Bodo Rosenhahn;Lei He;Reinhard Klette

  • Optimization and Filtering for Human Motion Capture

    Juergen Gall;Bodo Rosenhahn;Thomas Brox;Hans-Peter Seidel

  • Learning an Image-Based Motion Context for Multiple People Tracking

    Laura Leal-Taixé;Michele Fenzi;Alina Kuznetsova;Bodo Rosenhahn

  • Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs

    T. von Marcard;B. Rosenhahn;M. J. Black;G. Pons-Moll

  • Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection.

    Marco Rudolph;Tom Wehrbein;Bodo Rosenhahn;Bastian Wandt

  • RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation

    Bastian Wandt;Bodo Rosenhahn

  • Everybody needs somebody: Modeling social and grouping behavior on a linear programming multiple people tracker

    Laura Leal-Taixe;Gerard Pons-Moll;Bodo Rosenhahn

  • RelTR: Relation Transformer for Scene Graph Generation

    Unknown

  • Real-Time Sign Language Recognition Using a Consumer Depth Camera

    Alina Kuznetsova;Laura Leal-Taixe;Bodo Rosenhahn

  • Complementary Optic Flow

    Henning Zimmer;Andrés Bruhn;Joachim Weickert;Levi Valgaerts

  • Combined Region and Motion-Based 3D Tracking of Rigid and Articulated Objects

    T. Brox;B. Rosenhahn;J. Gall;D. Cremers

  • Human Pose Estimation from Video and IMUs

    Timo von Marcard;Gerard Pons-Moll;Bodo Rosenhahn

  • Multisensor-fusion for 3D full-body human motion capture

    Gerard Pons-Moll;Andreas Baak;Thomas Helten;Meinard Muller

  • Text to Image Generation with Semantic-Spatial Aware GAN.

    Kai Hu;Wentong Liao;Michael Ying Yang;Bodo Rosenhahn

  • Three-Dimensional Shape Knowledge for Joint Image Segmentation and Pose Tracking

    Bodo Rosenhahn;Thomas Brox;Joachim Weickert

  • Fusion of Head and Full-Body Detectors for Multi-object Tracking

    Roberto Henschel;Laura Leal-Taixe;Daniel Cremers;Bodo Rosenhahn

  • Markerless Motion Capture with unsynchronized moving cameras

    Nils Hasler;Bodo Rosenhahn;Thorsten Thormahlen;Michael Wand

  • Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs

    Timo von Marcard;Bodo Rosenhahn;Michael J. Black;Gerard Pons-Moll

Frequent Co-Authors

Michael Ying Yang
Michael Ying Yang University of Bath
Hans-Peter Seidel
Hans-Peter Seidel Max Planck Institute for Informatics
Thomas Brox
Thomas Brox University of Freiburg
Jörn Ostermann
Jörn Ostermann University of Hannover
Laura Leal-Taixé
Laura Leal-Taixé Technical University of Munich
Gerald Sommer
Gerald Sommer Kiel University
Reinhard Klette
Reinhard Klette Auckland University of Technology
Daniel Cremers
Daniel Cremers Technical University of Munich
Joachim Weickert
Joachim Weickert Saarland University
Gerard Pons-Moll
Gerard Pons-Moll University of Tübingen

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