Pascal Fua
EPFL IC IINFCOM CVLAB
BC 310 (Bâtiment BC)
Station 14
CH-1015 Lausanne
Biography
Pascal Fua received an engineering degree from Ecole Polytechnique, Paris, in 1984 and the Ph.D. degree in Computer Science from the University of Orsay in 1989. He then worked at SRI International and INRIA Sophia-Antipolis as a Computer Scientist. He joined EPFL in 1996 where he is now a Professor in the School of Computer and Communication Science and heads the Computer Vision Laboratory.
His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and Augmented Reality. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and Augmented Reality. He has (co)authored over 300 publications in refereed journals and conferences. He is an IEEE Fellow and has been an Associate Editor of IEEE journal Transactions for Pattern Analysis and Machine Intelligence. He often serves as program committee member, area chair, and program chair of major vision conferences and has cofounded two spinoff companies (Pix4D and PlayfulVision).
Current Work
The research activities of the Computer Vision Laboratory focus on shape and motion recovery from images, object and people detection and tracking in video sequences, and analysis of brain microscopy image-stacks. CVLab also provides undergraduate and graduate teaching and performs technology transfer to both established and start up companies.
Pascal Fua's research is sponsored by the Swiss National Science Foundation, the CTI, the European Union including a senior ERC grant, and several industrial partners.
Fields of expertise
Computer Vision, Biomedical Imaging, and Augmented Reality
Publications
Infoscience
All since 1996
Online data is not available2019
W. Liu; K. M. Lis; M. Salzmann; P. Fua : Geometric and Physical Constraints for Drone-Based Head Plane Crowd Density Estimation. 2019-11-08. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, November 4-8, 2019.
K. M. Lis; K. K. Nakka; P. Fua; M. Salzmann : Detecting the Unexpected via Image Resynthesis. 2019-10-27. ICCV 2019 : IEEE International Conference on Computer Vision, Seoul, South Korea, Oct 27, 2019 - Nov 3, 2019 .
W. Wang; P. Fua; K. Yu; J. Hugonot; M. Salzmann : Recurrent U-Net for Resource-Constrained Segmentation. 2019-10-27. International Conference on Computer Vision (ICCV 2019), Seoul, Korea, Oct 27 - Nov 3, 2019.
A. Maksai; P. Fua : Eliminating Exposure Bias and Metric Mismatch in Multiple Object Tracking. 2019-06-23. Computer Vision and Patter Recognition (CVPR), Long Beach, CA, June, 2019.
F. Bardi : Aerodynamic shape optimization via surrogate modelling with convolutional neural networks ; 2019-06-21.
L. Zampieri : Geometric Deep Learning for Volumetric Computational Fluid Dynamics ; 2019-06-21.
H. Rhodin; V. Constantin; I. Katircioglu; M. Salzmann; P. Fua : Neural Scene Decomposition for Multi-Person Motion Capture. 2019-06-20. Computer Vision and Patter Recognition (CVPR).
W. Liu; M. Salzmann; P. Fua : Context-Aware Crowd Counting. 2019-06-20. Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA, June 16-20, 2019.
Y. Hu; J. L. Hugonot; P. Fua; M. Salzmann : Segmentation-driven 6D Object Pose Estimation. 2019-06-16. Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, California, USA, June 16-20, 2019.
W. Xu; A. Chatterjee; M. Zollhofer; H. Rhodin; P. Fua et al. : Mo(2)Cap(2): Real-time Mobile 3D Motion Capture with a Cap-mounted Fisheye Camera; IEEE Transactions On Visualization And Computer Graphics (TOG). 2019-05-01. DOI : 10.1109/TVCG.2019.2898650.
K. Konyushkova; R. Sznitman; P. Fua : Geometry in active learning for binary and multi-class image segmentation; Computer Vision And Image Understanding (CVIU). 2019-05-01. DOI : 10.1016/j.cviu.2019.01.007.
B. Fan; Q. Kong; X. Wang; Z. Wang; S. Xiang et al. : A Performance Evaluation of Local Features for Image-Based 3D Reconstruction; IEEE Transactions on Image Processing (TIP). 2019-04-11. DOI : 10.1109/TIP.2019.2909640.
A. J. Mosinska / P. Fua (Dir.) : Learning Approach to Delineation of Curvilinear Structures in 2D and 3D Images. Lausanne, EPFL, 2019. DOI : 10.5075/epfl-thesis-9301.
A. J. Mosinska; M. Kozinski; P. Fua : Joint Segmentation and Path Classification of Curvilinear Structures; IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI). 2019.
A. Maksai / P. Fua (Dir.) : Training Algorithms for Multiple Object Tracking. Lausanne, EPFL, 2019. DOI : 10.5075/epfl-thesis-9203.
K. Konyushkova / P. Fua; R. Sznitman (Dir.) : Learning to Reduce Annotation Load. Lausanne, EPFL, 2019. DOI : 10.5075/epfl-thesis-9074.
2018
T. Bagautdinov; C. Wu; J. Saragih; Y. Sheikh; P. Fua : Modeling Facial Geometry using Compositional VAEs. 2018-06-18. Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, USA, June 18-22, 2018.
B. Tekin; S. N. Sinha; P. Fua : Real-Time Seamless Single Shot 6D Object Pose Prediction. 2018-06-18. Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA, 2018.
J. Bednarík; M. Salzmann; P. Fua : Learning to Reconstruct Texture-less Deformable Surfaces from a Single View. 2018-03-23. International Conference on 3D Vision, Verona, Italy, September 5-8, 2018.
I. Katiricioglu; B. Tekin; M. Salzmann; V. Lepetit; P. Fua : Learning Latent Representations of 3D Human Pose with Deep Neural Networks; International Journal of Computer Vision. 2018-01-31. DOI : 10.1007/s11263-018-1066-6.
M. Kozinski; A. Mosinska; M. Salzmann; P. Fua : Learning to Segment 3D Linear Structures Using Only 2D Annotations. 2018-01-01. 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Granada, SPAIN, Sep 16-20, 2018. p. 283-291. DOI : 10.1007/978-3-030-00934-2_32.
R. Achanta; P. Marquez Neila; P. Fua; S. Süsstrunk : Scale-Adaptive Superpixels. 2018. Color and Imaging Conference (CIC26), Vancouver, Canada, November 12-16, 2018. p. 1-6(6). DOI : 10.2352.
K. M. Yi; E. Trulls; Y. Ono; V. Lepetit; M. Salzmann et al. : Learning to Find Good Correspondences. 2018-01-01. Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, Jun 18-23, 2018. p. 2666-2674. DOI : 10.1109/CVPR.2018.00282.
H. Rhodin; J. Sporri; I. Katircioglu; V. Constantin; F. Meyer et al. : Learning Monocular 3D Human Pose Estimation from Multi-view Images. 2018-01-01. Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, Jun 18-23, 2018. p. 8437-8446. DOI : 10.1109/CVPR.2018.00880.
Y. Ono; E. Trulls; P. Fua; K. M. Yi : LF-Net: Learning Local Features from Images. 2018-01-01. 32nd Conference on Neural Information Processing Systems (NIPS), Montreal, CANADA, Dec 02-08, 2018.
B. Tekin; S. N. Sinha; P. Fua : Real-Time Seamless Single Shot 6D Object Pose Prediction. 2018-01-01. 31st IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, Jun 18-23, 2018. p. 292-301. DOI : 10.1109/CVPR.2018.00038.
Y. Ono; E. Trulls Fortuny; P. Fua; K. M. Yi : LF-Net: Learning Local Features from Images. 2018. Neural Information Processing Systems (NIPS), Montréal Canada.
R. Bermudez-Chancon; P. Marquez-Neila; M. Salzmann; P. Fua : A Domain-Adaptive Two-Stream U-Net For Electron Microscopy Image Segmentation. 2018-01-01. International Symposium on Biomedical Imaging (ISBI), Washington, DC, Apr 04-07, 2018. p. 400-404.
P. Baqué; E. Remelli; F. Fleuret; P. Fua : Geodesic Convolutional Shape Optimization. 2018. Proceedings of the International Conference on Machine Learning.
J. Bednarik; P. Fua; M. Salzmann : Learning to Reconstruct Texture-less Deformable Surfaces from a Single View. 2018-01-01. 6th International Conference on 3D Vision (3DV), Verona, ITALY, Sep 05-08, 2018. p. 606-615. DOI : 10.1109/3DV.2018.00075.
C. Cali; M. Wawrzyniak; C. Becker; B. Maco; M. Cantoni et al. : The effects of aging on neuropil structure in mouse somatosensory cortex-A 3D electron microscopy analysis of layer 1; PLOS ONE. 2018. DOI : 10.1371/journal.pone.0198131.
A. Crivellaro; M. Rad; Y. Verdie; K. Yi; P. Fua et al. : Robust 3D Object Tracking from Monocular Images Using Stable Parts; Transactions on Pattern Analysis and Machine Intelligence (PAMI). 2018. DOI : 10.1109/TPAMI.2017.2708711.
V. Paradiso; A. Crivellaro; K. Amgarou; N. de Lanaute; P. Fua et al. : A versatile calibration procedure for portable coded aperture gamma cameras and RGB-D sensors; NUCLEAR INSTRUMENTS AND METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT. 2018. DOI : 10.1016/j.nima.2017.12.065.
B. Tekin / P. Fua; V. Lepetit (Dir.) : Learning Robust Features and Latent Representations for Single View 3D Pose Estimation of Humans and Objects. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8753.
M. Kozinski; A. J. Mosinska; M. Salzmann; P. Fua : Learning to Segment 3D Linear Structures Using Only 2D Annotations. 2018. MICCAI, Granada, Spain, September 16-20, 2018.
A. Tkach / M. Pauly; A. Tagliasacchi (Dir.) : Real-Time Generative Hand Modeling and Tracking. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8573.
Z. Dang; K. M. Yi; Y. Hu; F. Wang; P. Fua et al. : Eigendecomposition-free Training of Deep Networks with Zero Eigenvalue-based Losses. 2018. European Conference on Computer Vision, Munich, Germany, September 8-14, 2018.
H. Rhodin; M. Salzmann; P. Fua : Unsupervised Geometry-Aware Representation Learning for 3D Human Pose Estimation. 2018. European Conference on Computer Vision (ECCV).
T. Chavdarova; P. Baqué; A. Maksai; S. Bouquet; C. Jose et al. : WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection. 2018. Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, Jun 18-23, 2018. p. 5030-5039. DOI : 10.1109/CVPR.2018.00528.
T. Bagautdinov / P. Fua; F. Fleuret (Dir.) : Variational Methods for Human Modeling. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8680.
P. B. Baqué / P. Fua; F. Fleuret (Dir.) : Mean-Field methods for Structured Deep-Learning in Computer Vision. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8677.
P. B. Baqué; E. Remelli; F. Fleuret; P. Fua : Geodesic Convolutional Shape Optimization. 2018. International Conference on Machine Learning (ICML), Stockholm, Sweden, July, 2018.
A. J. Mosinska; P. Marquez Neila; M. Kozinski; P. Fua : Beyond the Pixel-Wise Loss for Topology-Aware Delineation. 2018. Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, USA, June 18-22, 2018.
B. Jin / S. Süsstrunk (Dir.) : Computational Aesthetics and Image Enhancements using Deep Neural Networks. Lausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8420.
R. Bermúdez Chacón; P. Marquez Neila; M. Salzmann; P. Fua : A Domain-Adaptive Two-Stream U-Net for Electron Microscopy Image Segmentation. 2018. International Symposium of Biomedical Imaging (ISBI), Washington DC, USA, April 4-7, 2018.
H. Rhodin; J. Spörri; I. Katircioglu; V. Constantin; F. Meyer et al. : Learning Monocular 3D Human Pose Estimation from Multi-view Images. 2018. Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA.
A. Rozantsev; M. Salzmann; P. Fua : Residual Parameter Transfer for Deep Domain Adaptation. 2018. Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, USA, June 18-22, 2018.
K. M. Yi; E. Trulls Fortuny; Y. Ono; V. Lepetit; M. Salzmann et al. : Learning to Find Good Correspondences. 2018. Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, USA, June 18-22, 2018.
A. Rozantsev; M. Salzmann; P. Fua : Beyond Sharing Weights for Deep Domain Adaptation; IEEE Transactions on Pattern Analysis and Machine Intelligence. 2018. DOI : 10.1109/TPAMI.2018.2814042.
2017
P. Marquez Neila; M. Salzmann; P. Fua : Imposing Hard Constraints on Deep Networks: Promises and Limitations. 2017. CVPR Workshop on Negative Results in Computer Vision, Hawaii, HI, 2017.
K. Konyushkova; R. Sznitman; P. Fua : Learning Active Learning from Data. 2017. Advances in Neural Information Processing Systems.
A. Maksai; X. Wang; F. Fleuret; P. Fua : Non-Markovian Globally Consistent Multi-Object Tracking. 2017. Proceedings of the IEEE International Conference on Computer Vision.
P. Baqué; F. Fleuret; P. Fua : Deep Occlusion Reasoning for Multi-Camera Multi-Target Detection. 2017. Proceedings of the IEEE International Conference on Computer Vision.
P. Fua; V. Lepetit; A. Rozantsev; B. Tekin ; Method, System and Device for Direct Prediction of 3D Body Poses from Motion Compensated Sequence. US2017316578 . 2017.
M. A. Pinheiro; J. Kybic; P. Fua : Geometric Graph Matching Using Monte Carlo Tree Search; Transactions on Pattern Analysis and Machine Intelligence (PAMI). 2017. DOI : 10.1109/Tpami.2016.2636200.
T. Kurmann; P. Marquez Neila; X. Du; P. Fua; D. Stoyanov et al. : Simultaneous Recognition and Pose Estimation of Instruments in Minimally Invasive Surgery. 2017. International Conference on Medical Image Computing and Computer-Assisted Intervention (MCCAI), Quebec, Canada.
A. E. Ichim / M. Pauly (Dir.) : Physics-based Reconstruction and Animation of Humans. Lausanne, EPFL, 2017. DOI : 10.5075/epfl-thesis-7880.
E. Oveisi; A. Letouzey; D. Alexander; Q. Jeangros; R. Schäublin et al. : Tilt-less 3-D electron imaging and reconstruction of complex curvilinear structures; Scientific reports. 2017. DOI : 10.1038/s41598-017-07537-6.
N. Arvanitopoulos Darginis / S. Süsstrunk; R. Achanta (Dir.) : Sparse Gradient Optimization and its Applications in Image Processing. Lausanne, EPFL, 2017. DOI : 10.5075/epfl-thesis-7913.
E. Oveisi; A. Letouzey; S. De Zanet; G. Lucas; M. Cantoni et al. : Stereo-vision three-dimensional reconstruction of curvilinear structures imaged with a TEM; Ultramicroscopy. 2017. DOI : 10.1016/j.ultramic.2017.08.010.
D. Constantin / B. Merminod; Y. Akhtman (Dir.) : Miniature hyperspectral systems. Lausanne, EPFL, 2017. DOI : 10.5075/epfl-thesis-7647.
B. Tekin; P. Marquez Neila; M. Salzmann; P. Fua : Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation. 2017. International Conference on Computer Vision (ICCV).
E. Oveisi; A. Letouzey; P. Fua; C. Hébert : Three-dimensional electron imaging and reconstruction of dislocations from a single acquisition. 2017. Microscopy Conference, Lausanne, Switzerland.
T. Bagautdinov; A. Alahi; F. Fleuret; P. Fua; S. Savarese : Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition. 2017. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, USA, July 21-26, 2017. p. 3425-3434. DOI : 10.1109/Cvpr.2017.365.
E. Oveisi; S. De Zanet; P. Fua; C. Hébert : Computer Vision Techniques Applied to the Reconstruction of the 3-D Structure of Dislocations. 2017. Microscopy & Microanalysis, St Louis, MO, USA, 2017. p. 102-103. DOI : 10.1017/S1431927617001192.
A. J. Mosinska; J. Tarnawski; P. Fua : Active Learning and Proofreading for Delineation of Curvilinear Structures. 2017. MICCAI, Quebec City, Canada, September 10-14, 2017.
D. Mandl; K. M. Yi; P. Mohr; P. Roth; P. Fua et al. : Learning Lightprobes for Mixed Reality Illumination. 2017. International Symposium on Mixed and Augmented Reality (ISMAR), Nantes, France, October 9–13, 2017.
P. Baqué; F. Fleuret; P. Fua : Multi-Modal Mean-Fields via Cardinality-Based Clamping. 2017. CVPR 2017, Honolulu, Hawaii, USA, July 21-26, 2017. p. 4303-4312. DOI : 10.1109/Cvpr.2017.458.
A. Rozantsev / P. Fua; V. Lepetit (Dir.) : Vision-based detection of aircrafts and UAVs. Lausanne, EPFL, 2017. DOI : 10.5075/epfl-thesis-7589.
Other publications
| R. Achanta, A. Shaj, K. Smith, A. Lucchi, P. Fua, and S. S�sstrunk. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, num. 11, p. 2274 - 2282, 2012. |
SLIC Superpixels Compared to State-of-the-art Superpixel Methods |
| F Fleuret, J Berclaz, R Lengagne, and P Fua Pattern Analysis and Machine Intelligence, 30 (2), 267-282, 2008 |
Multicamera People Tracking with a Probabilistic Occupancy Map |
| V. Lepetit and P. Fua Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, Nr. 9, pp. 1465--1479, 2006. |
Keypoint Recognition using Randomized Trees |
| P. Fua and Y. G. Leclerc International Journal of Computer Vision, Vol. 16, pp. 35-56, 1995. |
Object-Centered Surface Reconstruction: Combining Multi-Image Stereo and Shading |
| P. Fua Machine Vision and Applications, Vol. 6, Nr. 1, pp. 35-49, 1993. |
A Parallel Stereo Algorithm that Produces Dense Depth Maps and Preserves Image Features |
Teaching & PhD
Teaching
- Computer Science,
- Communication Systems
PhD Programs
- Doctoral program in computer and communication sciences
- Doctoral Program in Electrical Engineering
PhD Students
Altingövde OkanBednarík Jan
Bermúdez Chacón Róger
Bhattacharjee Deblina
Guo Shuxuan
Günel Semih
Honzátko David
Katircioglu Isinsu
Kiciroglu Sena
Lis Krzysztof Maciej
Liu Weizhe
Nakka Krishna Kanth
Remelli Edoardo
Tyszkiewicz Michal Jan
Vidit Vidit
Wickramasinghe Pamuditha Udaranga
Yu Kaicheng
Past PhD Students
Ali Karim ...Bagautdinov Timur ...
Baqué Pierre Bruno ...
Becker Carlos Joaquin ...
Ben Shitrit Horesh Beny ...
Berclaz Jérôme ...
Calonder Michael ...
Crivellaro Alberto ...
Dimitrijevic Miodrag ...
Fossati Andrea ...
Glowacki Przemyslaw Rafal ...
González Serrano Germán ...
Herda Lorna ...
Ilic Slobodan ...
Konyushkova Ksenia ...
Lagger Pascal ...
Lucchi Aurélien ...
Maksai Andrii ...
Mosinska Agata Justyna ...
Ngo Tien Dat ...
Pilet Julien ...
Plänkers Ralf ...
Rigamonti Roberto ...
Rozantsev Artem ...
Salzmann Mathieu ...
Shahrokni Seyed Ali ...
Sironi Amos ...
Sun Xiaolu ...
Tekin Bugra ...
Tola Engin ...
Trzcinski Tomasz Piotr ...
Türetken Engin ...
Urtasun Raquel ...
Vacchetti Luca ...
Varol Aydin ...
Wang Xinchao ...
Özuysal Mustafa ...
Courses
Introduction to machine learning
Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. 
Computer vision