World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
65
Citations
20266
World Ranking
2428
National Ranking
103

Federico Tombari 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 Federico Tombari 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: 236 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Federico Tombari 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 Federico Tombari 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: 65 D-Index — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Overview

Federico Tombari is affiliated with the Technical University of Munich in Germany. Their research primarily spans the fields of Computer Science and Engineering, with a significant focus on Computer Vision and Pattern Recognition, Artificial Intelligence, and Computational Mechanics.

The scientist's work covers diverse topics including 3D Shape Modeling and Analysis, Advanced Vision and Imaging, Robotics and Sensor-Based Localization, Multimodal Machine Learning Applications, Advanced Neural Network Applications, Computer Graphics and Visualization Techniques, and Human Pose and Action Recognition.

Frequent publication venues for their work include:

  • arXiv (Cornell University)
  • IEEE Robotics and Automation Letters
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • International Journal of Computer Vision
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Selected recent papers authored or co-authored by Federico Tombari include:

  • "Neural Fields in Visual Computing and Beyond", 2022, Computer Graphics Forum
  • "Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language", 2022, arXiv (Cornell University)
  • "SHIFT: A Synthetic Driving Dataset for Continuous Multi-Task Domain Adaptation", 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimation", 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation", 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

The scientist has collaborated frequently with other researchers, including Nassir Navab, Fabian Manhardt, Luc Van Gool, Benjamin Busam, and Xiangyang Ji.

Federico Tombari has contributed scholarly books published by Springer Science+Business Media, including the title "Image Analysis and Processing - ICIAP 2022".

Best Publications

  • Deeper Depth Prediction with Fully Convolutional Residual Networks

    Iro Laina;Christian Rupprecht;Vasileios Belagiannis;Federico Tombari

  • Unique signatures of histograms for local surface description

    Federico Tombari;Samuele Salti;Luigi Di Stefano

  • SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again

    Wadim Kehl;Fabian Manhardt;Federico Tombari;Slobodan Ilic

  • SHOT: Unique signatures of histograms for surface and texture description

    Samuele Salti;Federico Tombari;Luigi Di Stefano

  • CNN-SLAM: Real-Time Dense Monocular SLAM with Learned Depth Prediction

    Keisuke Tateno;Federico Tombari;Iro Laina;Nassir Navab

  • Neural Fields in Visual Computing and Beyond

    Unknown

  • Tutorial: Point Cloud Library: Three-Dimensional Object Recognition and 6 DOF Pose Estimation

    A. Aldoma;Z. Marton;F. Tombari;W. Wohlkinger

  • BOP: Benchmark for 6D Object Pose Estimation

    Tomas Hodan;Frank Michel;Eric Brachmann;Wadim Kehl

  • Performance Evaluation of 3D Keypoint Detectors

    Federico Tombari;Samuele Salti;Luigi Di Stefano

  • GDR-Net: Geometry-Guided Direct Regression Network for Monocular 6D Object Pose Estimation

    Gu Wang;Fabian Manhardt;Federico Tombari;Xiangyang Ji

  • A combined texture-shape descriptor for enhanced 3D feature matching

    Federico Tombari;Samuele Salti;Luigi Di Stefano

  • Unique shape context for 3d data description

    Federico Tombari;Samuele Salti;Luigi Di Stefano

  • 3D Point Capsule Networks

    Yongheng Zhao;Tolga Birdal;Haowen Deng;Federico Tombari

  • Registration with the Point Cloud Library: A Modular Framework for Aligning in 3-D

    Dirk Holz;Alexandru E. Ichim;Federico Tombari;Radu B. Rusu

  • Deep Learning of Local RGB-D Patches for 3D Object Detection and 6D Pose Estimation

    Wadim Kehl;Fausto Milletari;Federico Tombari;Federico Tombari;Slobodan Ilic;Slobodan Ilic

  • Segmentation-based adaptive support for accurate stereo correspondence

    Federico Tombari;Stefano Mattoccia;Luigi Di Stefano

  • ZNCC-based template matching using bounded partial correlation

    Luigi Di Stefano;Stefano Mattoccia;Federico Tombari

  • Classification and evaluation of cost aggregation methods for stereo correspondence

    F. Tombari;S. Mattoccia;L. Di Stefano;E. Addimanda

  • Object Recognition in 3D Scenes with Occlusions and Clutter by Hough Voting

    Federico Tombari;Luigi Di Stefano

  • A global hypotheses verification method for 3d object recognition

    Aitor Aldoma;Federico Tombari;Luigi Di Stefano;Markus Vincze

  • OUR-CVFH – Oriented, Unique and Repeatable Clustered Viewpoint Feature Histogram for Object Recognition and 6DOF Pose Estimation

    Aitor Aldoma;Federico Tombari;Radu Bogdan Rusu;Markus Vincze

Frequent Co-Authors

Nassir Navab
Nassir Navab Technical University of Munich
Luigi Di Stefano
Luigi Di Stefano University of Bologna
Stefano Mattoccia
Stefano Mattoccia University of Bologna
Slobodan Ilic
Slobodan Ilic Technical University of Munich
Gregory D. Hager
Gregory D. Hager Johns Hopkins University
Radu Bogdan Rusu
Radu Bogdan Rusu Fyusion, Inc
Soheyl Noachtar
Soheyl Noachtar Ludwig-Maximilians-Universität München
Luca Benini
Luca Benini ETH Zurich
Michele Magno
Michele Magno ETH Zurich
Davide Brunelli
Davide Brunelli University of Trento

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