World's Best Scientists 2026 revealed!
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Computer Science
France
2025

D-Index & Metrics

Computer Science

D-Index
58
Citations
21929
World Ranking
3544
National Ranking
58

Research.com Recognitions

  • 2025 - Research.com Computer Science in France Leader Award
  • 2022 - Research.com Computer Science in France Leader Award

Overview

Jakob Verbeek is affiliated with Facebook AI Research (FAIR) in Paris, France. Their research primarily focuses on the field of computer science, with significant contributions in computer vision and pattern recognition as well as artificial intelligence.

The main research subfields Jakob Verbeek has worked in include:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Computational Mechanics
  • Computer Graphics and Computer-Aided Design
  • Geology

The scientist's work covers various topics relevant to the advancement of machine learning and image processing technologies. Their key research topics are:

  • Domain Adaptation and Few-Shot Learning
  • Generative Adversarial Networks and Image Synthesis
  • Advanced Neural Network Applications
  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • 3D Shape Modeling and Analysis
  • Advanced Image Processing Techniques

Jakob Verbeek has contributed to multiple research publications, frequently collaborating with notable co-authors such as Matthieu Cord, Alaaeldin El-Nouby, Marlène Careil, Hervé Jeǵou, and Hugo Touvron.

Among their recent papers are:

  • "ResMLP: Feedforward Networks for Image Classification With Data-Efficient Training" (2022), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "XCiT: Cross-Covariance Image Transformers" (2021), published on arXiv (Cornell University)
  • "DiffEdit: Diffusion-based semantic image editing with mask guidance" (2022), published on arXiv (Cornell University)
  • "FlexIT: Towards Flexible Semantic Image Translation" (2022), published at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Anytime Inference with Distilled Hierarchical Neural Ensembles" (2021), published in Proceedings of the AAAI Conference on Artificial Intelligence

Jakob Verbeek has published extensively, with a notable presence in venues including arXiv (Cornell University), IEEE Transactions on Pattern Analysis and Machine Intelligence, the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), the AAAI Conference on Artificial Intelligence, and the 2021 International Conference on 3D Vision (3DV).

Best Publications

  • The global k-means clustering algorithm

    Aristidis Likas;Nikos A. Vlassis;Jakob J. Verbeek

  • Image Classification with the Fisher Vector: Theory and Practice

    Jorge Sánchez;Florent Perronnin;Thomas Mensink;Jakob Verbeek

  • Is that you? Metric learning approaches for face identification

    Matthieu Guillaumin;Jakob Verbeek;Cordelia Schmid

  • Learning Color Names for Real-World Applications

    J. van de Weijer;C. Schmid;J. Verbeek;D. Larlus

  • TagProp: Discriminative metric learning in nearest neighbor models for image auto-annotation

    Matthieu Guillaumin;Thomas Mensink;Jakob Verbeek;Cordelia Schmid

  • ResMLP: Feedforward networks for image classification with data-efficient training

    Hugo Touvron;Piotr Bojanowski;Mathilde Caron;Matthieu Cord

  • Semantic Segmentation using Adversarial Networks

    Pauline Luc;Camille Couprie;Soumith Chintala;Jakob Verbeek

  • Multimodal semi-supervised learning for image classification

    Matthieu Guillaumin;Jakob Verbeek;Cordelia Schmid

  • Efficient greedy learning of Gaussian mixture models

    J. J. Verbeek;N. Vlassis;B. Kröse

  • Distance-Based Image Classification: Generalizing to New Classes at Near-Zero Cost

    T. Mensink;J. Verbeek;F. Perronnin;G. Csurka

  • Action and Event Recognition with Fisher Vectors on a Compact Feature Set

    Dan Oneata;Jakob Verbeek;Cordelia Schmid

  • Weakly Supervised Object Localization with Multi-Fold Multiple Instance Learning

    Ramazan Gokberk Cinbis;Jakob Verbeek;Cordelia Schmid

  • FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis

    Nitika Verma;Edmond Boyer;Jakob Verbeek

  • Metric learning for large scale image classification: generalizing to new classes at near-zero cost

    Thomas Mensink;Jakob Verbeek;Florent Perronnin;Gabriela Csurka

  • A Robust and Efficient Video Representation for Action Recognition

    Heng Wang;Dan Oneata;Jakob Verbeek;Cordelia Schmid

  • Region Classification with Markov Field Aspect Models

    J. Verbeek;B. Triggs

  • DiffEdit: Diffusion-based semantic image editing with mask guidance

    Unknown

  • Multi-fold MIL Training for Weakly Supervised Object Localization

    Ramazan Gokberk Cinbis;Jakob Verbeek;Cordelia Schmid

  • Accurate Image Search Using the Contextual Dissimilarity Measure

    H. Jegou;C. Schmid;H. Harzallah;J. Verbeek

  • Predicting Deeper into the Future of Semantic Segmentation

    Pauline Luc;Natalia Neverova;Camille Couprie;Jakob Verbeek

  • Learning Color Names from Real-World Images

    J. van de Weijer;C. Schmid;J. Verbeek

Frequent Co-Authors

Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA
Ben Kröse
Ben Kröse Amsterdam University of Applied Sciences
Nikos Vlassis
Nikos Vlassis Adobe Systems (United States)
Edmond Boyer
Edmond Boyer Meta for Business
Matthijs Douze
Matthijs Douze Facebook (United States)
Karteek Alahari
Karteek Alahari French Institute for Research in Computer Science and Automation - INRIA
Frédéric Jurie
Frédéric Jurie Université de Caen Normandie
Zaid Harchaoui
Zaid Harchaoui University of Washington

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