H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 103 Citations 56,145 468 World Ranking 130 National Ranking 4

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Pascal Fua spends much of his time researching Artificial intelligence, Computer vision, Pattern recognition, Robustness and Image processing. Artificial intelligence is closely attributed to Machine learning in his research. Pascal Fua combines subjects such as Pixel, Deep learning and Histogram with his study of Pattern recognition.

His research integrates issues of Animation, Image gradient, Image registration and Dynamic programming in his study of Robustness. The concepts of his Image processing study are interwoven with issues in Cognitive neuroscience of visual object recognition and Pattern recognition. His research in Pattern recognition tackles topics such as Stereopsis which are related to areas like Algorithm.

His most cited work include:

  • SLIC Superpixels Compared to State-of-the-Art Superpixel Methods (5080 citations)
  • BRIEF: binary robust independent elementary features (2306 citations)
  • EPnP: An Accurate O(n) Solution to the PnP Problem (1399 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Pose. As part of his studies on Artificial intelligence, Pascal Fua often connects relevant subjects like Machine learning. His research links Robustness with Computer vision.

His Pattern recognition study incorporates themes from Pixel and Feature. His primary area of study in Pose is in the field of 3D pose estimation. He is interested in Image segmentation, which is a branch of Segmentation.

He most often published in these fields:

  • Artificial intelligence (84.38%)
  • Computer vision (58.72%)
  • Pattern recognition (21.87%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (84.38%)
  • Computer vision (58.72%)
  • Pattern recognition (21.87%)

In recent papers he was focusing on the following fields of study:

His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Deep learning and Segmentation. His research on Artificial intelligence often connects related areas such as Machine learning. His study in the fields of 3D pose estimation, RGB color model and Motion under the domain of Computer vision overlaps with other disciplines such as Key.

His research in Pattern recognition intersects with topics in Domain, Leverage and Scale. Pascal Fua studied Deep learning and Algorithm that intersect with Surface reconstruction, Eigendecomposition of a matrix and Point cloud. His Image segmentation study, which is part of a larger body of work in Segmentation, is frequently linked to Encoder, bridging the gap between disciplines.

Between 2018 and 2021, his most popular works were:

  • Beyond Sharing Weights for Deep Domain Adaptation (231 citations)
  • Context-Aware Crowd Counting (147 citations)
  • Segmentation-Driven 6D Object Pose Estimation (81 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Machine learning

His primary areas of investigation include Artificial intelligence, Computer vision, Pattern recognition, Deep learning and Pose. Artificial intelligence and Key are two areas of study in which Pascal Fua engages in interdisciplinary work. In the field of Computer vision, his study on Motion capture, 3D pose estimation and Crowd counting overlaps with subjects such as Fuse.

Pascal Fua works mostly in the field of Pattern recognition, limiting it down to topics relating to Leverage and, in certain cases, Shape reconstruction, Surface reconstruction, Metric tensor, Point cloud and Algorithm. His Deep learning study combines topics in areas such as Video tracking, Sequence, Categorization and Proxy. His Pose study integrates concerns from other disciplines, such as Monocular, Focal length, Image sequence and Robustness.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

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

R. Achanta;A. Shaji;K. Smith;A. Lucchi.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)

6493 Citations

BRIEF: binary robust independent elementary features

Michael Calonder;Vincent Lepetit;Christoph Strecha;Pascal Fua.
european conference on computer vision (2010)

3720 Citations

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

Vincent Lepetit;Francesc Moreno-Noguer;Pascal Fua.
International Journal of Computer Vision (2009)

1759 Citations

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

E. Tola;V. Lepetit;P. Fua.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2010)

1503 Citations

Multiple Object Tracking Using K-Shortest Paths Optimization

J. Berclaz;F. Fleuret;E. Turetken;P. Fua.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2011)

987 Citations

Keypoint recognition using randomized trees

V. Lepetit;P. Fua.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

965 Citations

Fast Keypoint Recognition Using Random Ferns

M. Ozuysal;M. Calonder;V. Lepetit;P. Fua.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2010)

860 Citations

Multicamera People Tracking with a Probabilistic Occupancy Map

F. Fleuret;J. Berclaz;R. Lengagne;P. Fua.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2008)

856 Citations

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

C. Strecha;W. von Hansen;L. Van Gool;P. Fua.
computer vision and pattern recognition (2008)

810 Citations

BRIEF: Computing a Local Binary Descriptor Very Fast

M. Calonder;V. Lepetit;M. Ozuysal;T. Trzcinski.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)

763 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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Top Scientists Citing Pascal Fua

Luc Van Gool

Luc Van Gool

ETH Zurich

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Marc Pollefeys

ETH Zurich

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Technical University of Munich

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University of Clermont Auvergne

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Max Planck Institute for Informatics

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Bodo Rosenhahn

Bodo Rosenhahn

University of Hannover

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Horst Bischof

Horst Bischof

Graz University of Technology

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Vincent Lepetit

Vincent Lepetit

École Normale Supérieure

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Konrad Schindler

Konrad Schindler

ETH Zurich

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Francesc Moreno-Noguer

Francesc Moreno-Noguer

Spanish National Research Council

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Qi Tian

Qi Tian

Huawei Technologies (China)

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Hans-Peter Seidel

Hans-Peter Seidel

Max Planck Institute for Informatics

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Torsten Sattler

Torsten Sattler

Czech Technical University in Prague

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Gerard Medioni

Amazon (United States)

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Slobodan Ilic

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