Research talks, keynotes and tutorials

2022.10: Plenary talk at ICIP’22: TBC.
2022.07: Course at the Vision and Sport Summer School (VS3 2022) in Prague: Robustness and adaptation.
2022.06: Keynote at the Vision4AllSeaons CVPR Workshop: TBC
2022.05: Keynote at the Autonomy2.0 ICRA Workshop: TBC
2022.02: Talk at EPFL CV Seminar: Annotation-efficient perception for driving [video].
2022.01: IMT podcast (in French): Challenges of driving automation.
2022.01: Keynote on trustworthy AI at the French Academy of Technologies
2022.01: Keynote at Eurecom: On basic AI research in corporate labs.
2021.11: Keynote at the ACM-Computer Science in Cars Symposium (CSCS): Annotation-efficient perception for driving.
2021.11: Panel on AI at Institut Henri Pointcaré
2021.11: Panel on autonomous vehicles at the AI Day of the French AI Manifesto
2021.10: Panel on Machine Learning and Physics at the Industry Day on AI of the French Physics Society
2021.06: Keynote at Vision4AllSeason CVPR’21 workhsop: Some challenges of night-time perception for driving.
2021.06: Keynote at the Airbus workshop: Frugal learning for autonomous driving.
2021.06: Keynote at SAIAD CVPR’21 workhsop: Paying attention to pedestrians.
2021.05: Keynote at Mobilit.AI: Challenges of AI for AD [video] and panel on embedded AI.
2021.04: Keynote at Good In Tech: Manipulating visual content in the age of modern AI.
2021.03: Panel on Math and AI.
2021.02: Industrial panel at Visigrapp 2021: Transfers from research to applications.
2020.12: Keynote at ML4AD NeurIPS’20 workshop: Addressing some challenges of ML4AD [video].
2020.11: Research talk at NaverLabs Europe: Safer driving AI with limited supervision.
2020.10: Research talk at Samsung AI Cambridge Center: Safer driving AI with limited supervision.
2020.09: Tutorial for French Home Affairs Ministry: Safer driving AI with limited supervision.
2020.06: Keynote at SAIAD CVPR’20 workhsop: Toward safer driving AI [video].
2019.11: Panel on Maths and AI at Poincaré Institute, Paris.
2019.10: Course at PAISS’19: Autonomous driving & sustainable supervision.
2019.10: Panel on Future Mobilities at PRAIRIE inauguration day.
2019.06: Keynote at SAIAD CVPR’19 workhsop: Sustainable supervision with application to autonomous driving
2019.06: Research talk at INRIA Grenoble: Unsupervised domain adaptation with application to urban scene analysis.
2019.06: Tutorial at IMT Atlantique: Unsupervised domain adaptation with application to urban scene analysis.
2019.04: Tutorial at Praque ML Meetup: Unsupervised domain adaptation with application to urban scene analysis.
2019.04: Research talk at CTU Prague: AdvEnt: Adversarial Entropy Minimization for domain adaptation in semantic segmentations.
2019.03: Keynote at AI & Physics (Pascal Institute, Orsay): Attacking inverse problems with deep learning.
2019.03: Kyenote at Imaging & Machine Learnning: Unsupervised domain adaptation with application to urban scene analysis.
2019.03: Keynote at Computing and Learning: Fast neural solvers.
2018.11: Keynote at SophI.A.2018: Movies & Cars: When visual deep learning reinvent two secular industries
2018.11: Keynote at Horizon Maths 2018 : Intelligence Artificielle: Fast neural solvers [video].
2018.11: Keynote at European Cyber Week 2018: Manipulating visual content in the age of modern AI.
2018.07: Course at “Peyresq Summer School on Signal and Image Processing”: Introduction to deep learning.
2018.02: Tutorial at Rennes ML MeetUp: Deep learning for the movie industry.
2017.12: Tutorial at Inria Rennes: Gentle introduction to deep learning.
2017.11: Tutorial at Université Pierre et Marie Curie: Deep learning for the movie industry.
2017.10: Research talk at Inria Grenoble: Graph signals and neural nets.
2017.09: Research talk at Inria Rennes: Graph signals and neural nets.
2017.09: Tutorial at Université Jean Monnet, St-Etienne: Deep learning for the movie industry.
2017.06: Research talk at Google Brain Montreal: From processing to learning on graphs.
2017.04: Research talk at Google Research Zurich: From processing to learning on graphs.
2017.03: Tutorial at French Research Ministry: AI and Industry.
2017.03: Research talk at Institut Poincaré: From processing to learning on graphs.
2017.01: Tutorial at Inria Paris: From video objects to visual effects.
2016.09: Keynote at DAGM: On visual comparison.
2016.07: Keynote at RFIA’16: Manipulating objects and scenes in video postprod.
2016.04: Keynote at StatLearn’16: On visual comparison.
2016.03: Andrew Blake celebration talk at Microsoft Research Cammbridge: From image to video inpainting.
2015.10: Tutorial at CNRS working group: Visual tracking of arbitrary objects.
2015.10: Research talk at CNRS working group: From image to video inpainting with patches.
2015.09: Research talk at Inria Sophia Antipolis: Manipulating videos objects: from removal to retargeting.
2015.07: Research talk at Facebook AI Research: Learned visual embeddings.
2015.07: Research talk at Inria Grenoble: Learned visual embeddings.
2015.06: Keynote at MissData’15: From image to video inpainting with patches.
2015.05: Research talk at Ircam: On audio-visual research at Technicolor.
2015.01: Research talk at Tel-Aviv University: From image to video inpainting with patches.
2014.10: Research talk at Oxford University: Face2face: comparing faces, with applications.
2014.10: Research talk at Inria Rennes: Face2face: comparing faces, with applications.
2014.08: Course at the VS3 Summer School: Visual tracking.
2014.06: Tutorial at Centrale Marseille: Computer vision in everyday life.
2014.06: Keynote at ICISP’14: From image to video inpainting with patches.
2014.04: Keynote at JMAIB’14: From image to video inpainting with patches.
2014.01: Research talk at Telecom Paris: From images to descriptors, and back again.
2014.01: Research talk at Paris ML Meetup: From images to descriptors, and back again.
2014.01: Research talk at MIA’14: From images to descriptors, and back again.
2013.07: Course at Inria/ENS VRML Summer School: A glimpse at visual tracking.
2013.06: Tutorial at Centrale Marseille: Computer vision in everyday life.
2012.10: Research talk at Inria Grenoble: Dense correspondences in long videos.
2012.09: Research talk at MPI Saarbruken: On visual search.
2012.08: Course at VS3 Summer School: Visual tracking.
2012.03: Research talk at Oxford Brookes: On visual search.
2012.02: Tutorial at Inria Rennes: Visual tracking & particle filters.
2012.01: Tutorial at Inria Grenoble: Visual tracking.
2011.12: Tutorial at Centrale Marseille: Computer vision in everyday life.
2011.08: Course at VS3 Summer School: Visual tracking.
2011.06: Research talk at MPI Saarbrucken: Geodesic image and video editing.
2011.05: Keynote at Orasis’11: About Research and R&D in computer vision.
2011.04: Tutorial at Stanford University: On visual search.
2010.07: Course at ICVSS Summer School: Viewpoint and pose invariant video analysis.
2010.05: Research talk at ENS Cachan: Geodesic image and video editing.
2009.12: Research talk at MIA’09: Track2x: Video analysis with point tracks.
2008.09: Research talk at Copenhagen University: Robust visual tracking with background analysis.
2008.01: Research talk at Montevideo Universtiy: About patches.
2007.10: Research talk Microsoft Research Cambridge: Image change detection.
2007.05: Research talk at Inria Rennes: Image surgery.
2006.12: Keynote at IAIP Eindhoben: Tracking, mixtures and particles.
2006.11: Research talk at CNRS workshop: Robust visual tracking with background analysis.
2006.09: Keynote at IDIAP 15th Aniversary: 15 years of computer vision: a visual tracking perspective.
2006.07: Course at Peyresq Summer School: Monte Carlo methods for image and video analysis.
2006.03: Research talk at Microsoft Research Cambridge: Figure/ground tracking and conditional filters.
2005.10: Research talk at Inria Sophia Antipolis: Tracking, mixtures and particles.
2005.06: Research talk at Microsoft Research Cambridge: Bayesian tracking with discrete auxiliary process.
2003.12: Course at Cambridge University: Texture in/from real images.
2002.12: Research talk at Institut Poincaré: Pixels and Particles: Sequential Monte Carlo for image analysis.

Patrick Pérez