World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
73
Citations
26622
World Ranking
1560
National Ranking
814

Vittorio Ferrari 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 Vittorio Ferrari 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: 227 publications — 56th percentile

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

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

Vittorio Ferrari 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 Vittorio Ferrari 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: 73 D-Index — 89th percentile

89% of scientists in this discipline score the same or lower.

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

Overview

Vittorio Ferrari is a researcher affiliated with Google in the United States, specializing in the field of Computer Science. Their primary research focus lies in Computer Vision and Pattern Recognition, which constitutes the majority of their published work. In addition to this, their research spans areas within Artificial Intelligence, Computational Mechanics, Computer Graphics and Computer-Aided Design, and Radiology, Nuclear Medicine and Imaging.

The main topics covered in Ferrari's research include Advanced Vision and Imaging, Domain Adaptation and Few-Shot Learning, Multimodal Machine Learning Applications, Advanced Image and Video Retrieval Techniques, Advanced Neural Network Applications, 3D Shape Modeling and Analysis, and Computer Graphics and Visualization Techniques.

Vittorio Ferrari has contributed to a substantial number of scientific publications with a diversified presence across prominent venues. Frequent publication venues include arXiv (Cornell University) with 28 publications, the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) with 5 publications, Lecture Notes in Computer Science with 3 publications, International Journal of Computer Vision with 2 publications, and the 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) with 2 publications.

Some notable recent papers include:

  • The Open Images Dataset V4, 2020, International Journal of Computer Vision
  • C-Flow: conditional generative flow models for images and 3D point clouds, 2020, UPCommons (Polytechnic University of Catalonia)
  • Transferability Estimation using Bhattacharyya Class Separability, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • ShaRF: Shape-conditioned Radiance Fields from a Single View, 2021, arXiv (Cornell University)
  • Neural Radiance Fields Approach to Deep Multi-View Photometric Stereo, 2022, 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

Vittorio Ferrari frequently collaborates with several coauthors. These include:

  • Jasper Uijlings
  • Thomas Mensink
  • Stefan Popov
  • Luc Van Gool
  • Berk Kaya

The researcher's body of work reflects an extensive engagement with machine learning approaches and image-based modeling, combining theoretical methods and practical applications across computer vision, graphics, and imaging modalities. No records of book publications or awards were specified.

Best Publications

  • The Open Images Dataset V4: Unified Image Classification, Object Detection, and Visual Relationship Detection at Scale

    Alina Kuznetsova;Hassan Rom;Neil Alldrin;Jasper R. R. Uijlings

  • Measuring the Objectness of Image Windows

    B. Alexe;T. Deselaers;V. Ferrari

  • What is an object

    Bogdan Alexe;Thomas Deselaers;Vittorio Ferrari

  • COCO-Stuff: Thing and Stuff Classes in Context

    Holger Caesar;Jasper Uijlings;Vittorio Ferrari

  • What’s the Point: Semantic Segmentation with Point Supervision

    Amy L. Bearman;Olga Russakovsky;Vittorio Ferrari;Li Fei-Fei

  • ClassCut for unsupervised class segmentation

    Bogdan Alexe;Thomas Deselaers;Vittorio Ferrari

  • Progressive search space reduction for human pose estimation

    V. Ferrari;M. Marin-Jimenez;A. Zisserman

  • Groups of Adjacent Contour Segments for Object Detection

    V. Ferrari;L. Fevrier;F. Jurie;C. Schmid

  • Fast Object Segmentation in Unconstrained Video

    Anestis Papazoglou;Vittorio Ferrari

  • Segmentation propagation in imagenet

    Daniel Kuettel;Matthieu Guillaumin;Vittorio Ferrari

  • Object detection by contour segment networks

    Vittorio Ferrari;Tinne Tuytelaars;Luc Van Gool

  • Learning object class detectors from weakly annotated video

    Alessandro Prest;Christian Leistner;Javier Civera;Cordelia Schmid

  • Learning Visual Attributes

    Vittorio Ferrari;Andrew Zisserman

  • The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale

    Alina Kuznetsova;Hassan Rom;Neil Alldrin;Jasper Uijlings

  • From Images to Shape Models for Object Detection

    Vittorio Ferrari;Frederic Jurie;Cordelia Schmid

  • Action Tubelet Detector for Spatio-Temporal Action Localization

    Vicky Kalogeiton;Philippe Weinzaepfel;Vittorio Ferrari;Cordelia Schmid

  • Weakly Supervised Localization and Learning with Generic Knowledge

    Thomas Deselaers;Bogdan Alexe;Vittorio Ferrari

  • Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

    Carina Silberer;Vittorio Ferrari;Mirella Lapata

  • Towards Multi-View Object Class Detection

    A. Thomas;V. Ferrar;B. Leibe;T. Tuytelaars

  • Simultaneous Object Recognition and Segmentation by Image Exploration

    Vittorio Ferrari;Tinne Tuytelaars;Luc J. Van Gool

  • Computer Vision (ICCV), 2011 IEEE International Conference on

    Alexander Vezhnevets;Vittorio Ferrari;J.M. Buhmann

  • Proceedings of the 5th International Conference on Image and Video Retrieval

    Till Quack;Vittorio Ferrari;Luc Van Gool

Frequent Co-Authors

Jasper Uijlings
Jasper Uijlings Google (United States)
Luc Van Gool
Luc Van Gool Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)
Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA
Andrew Zisserman
Andrew Zisserman University of Oxford
Thomas Deselaers
Thomas Deselaers Apple (United States)
Frédéric Jurie
Frédéric Jurie Université de Caen Normandie
Frank Keller
Frank Keller University of Edinburgh
Christoph H. Lampert
Christoph H. Lampert Institute of Science and Technology Austria

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