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Computer Science

D-Index
73
Citations
26622
World Ranking
1560
National Ranking
813

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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