World's Best Scientists 2026 revealed!
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Computer Science
Switzerland
2026

D-Index & Metrics

Computer Science

D-Index
116
Citations
72307
World Ranking
171
National Ranking
5

Research.com Recognitions

  • 2026 - Research.com Computer Science in Switzerland Leader Award
  • 2025 - Research.com Computer Science in Switzerland Leader Award
  • 2023 - Research.com Computer Science in Switzerland Leader Award
  • 2022 - Research.com Computer Science in Switzerland Leader Award

Overview

Pascal Fua is affiliated with the École Polytechnique Fédérale de Lausanne in Switzerland. Their research predominantly spans the fields of Computer Science and Engineering, with a particular focus on Computer Vision and Pattern Recognition, Computational Mechanics, and Computer Graphics and Computer-Aided Design. Additional subfields include Artificial Intelligence and Environmental Engineering.

The scientist's main research topics cover areas such as 3D Shape Modeling and Analysis, Computer Graphics and Visualization Techniques, Human Pose and Action Recognition, Advanced Vision and Imaging, Video Surveillance and Tracking Methods, Advanced Neural Network Applications, and Medical Image Segmentation Techniques.

Pascal Fua has contributed numerous papers to various reputable publication venues. Frequent venues for their work include arXiv (Cornell University), Zenodo (CERN European Organization for Nuclear Research), IEEE Transactions on Pattern Analysis and Machine Intelligence, the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), and Nature Methods.

Recent papers authored or co-authored by Pascal Fua include:

  • DISK: Learning local features with policy gradient, 2020, arXiv (Cornell University)
  • LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals, 2021, Nature Methods
  • SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation, 2021, arXiv (Cornell University)
  • Generating LOD3 building models from structure-from-motion and semantic segmentation, 2022, Automation in Construction
  • Robust Differentiable SVD, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence

Pascal Fua has frequently collaborated with several co-authors, including Mathieu Salzmann, Sina Honari, Mateusz Koziński, Benoît Guillard, and Doruk Öner. Collaborative efforts with these researchers form a significant portion of their published work.

Best Publications

  • SLIC Superpixels Compared to State-of-the-Art Superpixel Methods

    R. Achanta;A. Shaji;K. Smith;A. Lucchi

  • BRIEF: binary robust independent elementary features

    Michael Calonder;Vincent Lepetit;Christoph Strecha;Pascal Fua

  • EPnP: An Accurate O(n) Solution to the PnP Problem

    Vincent Lepetit;Francesc Moreno-Noguer;Pascal Fua

  • DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo

    E. Tola;V. Lepetit;P. Fua

  • LIFT: Learned Invariant Feature Transform

    Kwang Moo Yi;Eduard Trulls;Vincent Lepetit;Pascal Fua

  • Multiple Object Tracking Using K-Shortest Paths Optimization

    J. Berclaz;F. Fleuret;E. Turetken;P. Fua

  • Monocular 3D Human Pose Estimation in the Wild Using Improved CNN Supervision

    Dushyant Mehta;Helge Rhodin;Dan Casas;Pascal Fua

  • Multicamera People Tracking with a Probabilistic Occupancy Map

    F. Fleuret;J. Berclaz;R. Lengagne;P. Fua

  • Keypoint recognition using randomized trees

    V. Lepetit;P. Fua

  • BRIEF: Computing a Local Binary Descriptor Very Fast

    M. Calonder;V. Lepetit;M. Ozuysal;T. Trzcinski

  • On benchmarking camera calibration and multi-view stereo for high resolution imagery

    C. Strecha;W. von Hansen;L. Van Gool;P. Fua

  • Discriminative Learning of Deep Convolutional Feature Point Descriptors

    Edgar Simo-Serra;Eduard Trulls;Luis Ferraz;Iasonas Kokkinos

  • Fast Keypoint Recognition Using Random Ferns

    M. Ozuysal;M. Calonder;V. Lepetit;P. Fua

  • Real-Time Seamless Single Shot 6D Object Pose Prediction

    Bugra Tekin;Sudipta N. Sinha;Pascal Fua

  • Monocular Model-Based 3D Tracking of Rigid Objects: A Survey

    Vincent Lepetit;Pascal Fua

  • Gradient Response Maps for Real-Time Detection of Textureless Objects

    S. Hinterstoisser;C. Cagniart;S. Ilic;P. Sturm

  • LDAHash: Improved Matching with Smaller Descriptors

    C. Strecha;A. M. Bronstein;M. M. Bronstein;P. Fua

  • Randomized trees for real-time keypoint recognition

    V. Lepetit;P. Lagger;P. Fua

  • A fast local descriptor for dense matching

    E. Tola;V. Lepetit;P. Fua

  • Context-Aware Crowd Counting

    Weizhe Liu;Mathieu Salzmann;Pascal Fua

  • Fast Keypoint Recognition in Ten Lines of Code

    M. Ozuysal;P. Fua;V. Lepetit

Frequent Co-Authors

Vincent Lepetit
Vincent Lepetit École des Ponts ParisTech
Mathieu Salzmann
Mathieu Salzmann École Polytechnique Fédérale de Lausanne
Xinchao Wang
Xinchao Wang National University of Singapore
Slobodan Ilic
Slobodan Ilic Technical University of Munich
Raquel Urtasun
Raquel Urtasun University of Toronto
Daniel Thalmann
Daniel Thalmann École Polytechnique Fédérale de Lausanne
Graham Knott
Graham Knott École Polytechnique Fédérale de Lausanne
Francesc Moreno-Noguer
Francesc Moreno-Noguer Universitat Politècnica de Catalunya
Nassir Navab
Nassir Navab Technical University of Munich

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