Pascal Fua
Impact in
- Computer Vision and Pattern Recognition top 0.01%
- Advanced Image and Video Retrieval Techniques
- Advanced Vision and Imaging
- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
- Advanced Neural Network Applications
- Image Retrieval and Classification Techniques
- Aerospace Engineering top 0.01%
- Robotics and Sensor-Based Localization
Papers in
-
- Advanced Vision and Imaging 178
- Advanced Image and Video Retrieval Techniques 89
- Human Pose and Action Recognition 80
- Video Surveillance and Tracking Methods 77
- Medical Image Segmentation Techniques 59
-
- Robotics and Sensor-Based Localization 119
- Co-authors
- Vincent Lepetit (91 shared papers)Aurélien Lucchi (12 shared papers)Kevin Smith (9 shared papers)Radhakrishna Achanta (8 shared papers)Christoph Strecha (15 shared papers)Sabine Süsstrunk (6 shared papers)Anil Shaji (2 shared papers)Michael Calonder (8 shared papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (44 papers)Computer Vision and Image Understanding (15 papers)International Journal of Computer Vision (12 papers)Machine Vision and Applications (9 papers)Lecture notes in computer science (72 papers)
- Partner nations
- SwitzerlandUnited StatesFrance
In The Last Decade
Pascal Fua
464 papers receiving 38.0k citations
Pascal Fua's Hit Papers
Peers
Comparison fields: 5 of 199
- Computer Vision and Pattern Recognition 31.2k
- Aerospace Engineering 12.6k
- Geology 2.8k
- Media Technology 3.9k
- Computer Graphics and Computer-Aided Design 1.3k
Countries citing papers authored by Pascal Fua
This map shows the geographic impact of Pascal Fua's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Pascal Fua with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pascal Fua more than expected).
Fields of papers citing papers by Pascal Fua
This network shows the impact of papers produced by Pascal Fua. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pascal Fua. The network helps show where Pascal Fua may publish in the future.
Co-authors
The 25 scholars most cited alongside Pascal Fua, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 479 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | SLIC Superpixels Compared to State-of-the-Art Superpixel Methods Hit paper breakdown → | 2012 | 7003 |
| 2 | BRIEF: Binary Robust Independent Elementary Features Hit paper breakdown → | 2010 | 2689 |
| 3 | EPnP: An Accurate O(n) Solution to the PnP Problem Hit paper breakdown → | 2008 | 2294 |
| 4 | DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo Hit paper breakdown → | 2009 | 1051 |
| 5 | LIFT: Learned Invariant Feature Transform Hit paper breakdown → | 2016 | 827 |
| 6 | Multiple Object Tracking Using K-Shortest Paths Optimization Hit paper breakdown → | 2011 | 776 |
| 7 | Monocular 3D Human Pose Estimation in the Wild Using Improved CNN Supervision Hit paper breakdown → | 2017 | 725 |
| 8 | BRIEF: Computing a Local Binary Descriptor Very Fast Hit paper breakdown → | 2011 | 654 |
| 9 | Multicamera People Tracking with a Probabilistic Occupancy Map Hit paper breakdown → | 2007 | 636 |
| 10 | On benchmarking camera calibration and multi-view stereo for high resolution imagery Hit paper breakdown → | 2008 | 628 |
| 11 | Real-Time Seamless Single Shot 6D Object Pose Prediction Hit paper breakdown → | 2018 | 616 |
| 12 | Keypoint recognition using randomized trees Hit paper breakdown → | 2006 | 546 |
| 13 | Context-Aware Crowd Counting Hit paper breakdown → | 2019 | 508 |
| 14 | Fast Keypoint Recognition Using Random Ferns Hit paper breakdown → | 2009 | 484 |
| 15 | LDAHash: Improved Matching with Smaller Descriptors Hit paper breakdown → | 2011 | 473 |
| 16 | Gradient Response Maps for Real-Time Detection of Textureless Objects Hit paper breakdown → | 2011 | 441 |
| 17 | Monocular Model-Based 3D Tracking of Rigid Objects: A Survey Hit paper breakdown → | 2005 | 412 |
| 18 | Monocular Model-Based 3D Tracking of Rigid Objects: A Survey Hit paper breakdown → | 2005 | 391 |
| 19 | A fast local descriptor for dense matching Hit paper breakdown → | 2008 | 367 |
| 20 | 1993 | 354 |
About Pascal Fua
Pascal Fua is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Computational Mechanics, Computer Graphics and Computer-Aided Design and Artificial Intelligence, having authored 479 papers that have together received 39.8k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (178 papers), Robotics and Sensor-Based Localization (119 papers), Advanced Image and Video Retrieval Techniques (89 papers), Human Pose and Action Recognition (80 papers), 3D Shape Modeling and Analysis (80 papers), Video Surveillance and Tracking Methods (77 papers), Computer Graphics and Visualization Techniques (64 papers) and Medical Image Segmentation Techniques (59 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (31.2k citations), Aerospace Engineering (12.6k citations), Geology (2.8k citations), Media Technology (3.9k citations) and Computer Graphics and Computer-Aided Design (1.3k citations). Pascal Fua has collaborated with scholars based in Switzerland, United States and France. Frequent co-authors include Vincent Lepetit, Aurélien Lucchi, Kevin Smith, Radhakrishna Achanta, Christoph Strecha, Sabine Süsstrunk, Anil Shaji, Michael Calonder, Francesc Moreno-Noguer and Mathieu Salzmann. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Computer Vision and Image Understanding, International Journal of Computer Vision, Machine Vision and Applications and Lecture notes in computer science.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.