1 code implementation • 12 Dec 2023 • Patrik Vacek, David Hurych, Karel Zimmermann, Patrick Perez, Tomas Svoboda
Learning without supervision how to predict 3D scene flows from point clouds is essential to many perception systems.
1 code implementation • 1 Dec 2023 • Loick Chambon, Eloi Zablocki, Mickael Chen, Florent Bartoccioni, Patrick Perez, Matthieu Cord
To address this, we propose PointBeV, a novel sparse BeV segmentation model operating on sparse BeV cells instead of dense grids.
no code implementations • 24 Nov 2023 • Eslam Mohamed BAKR, Liangbing Zhao, Vincent Tao Hu, Matthieu Cord, Patrick Perez, Mohamed Elhoseiny
Diffusion-based generative models excel in perceptually impressive synthesis but face challenges in interpretability.
1 code implementation • 13 Jul 2022 • Awet Haileslassie Gebrehiwot, Patrik Vacek, David Hurych, Karel Zimmermann, Patrick Perez, Tomáš Svoboda
We propose to leverage sequences of point clouds to boost the pseudolabeling technique in a teacher-student setup via training multiple teachers, each with access to different temporal information.
no code implementations • 29 Sep 2021 • Charles Corbière, Marc Lafon, Nicolas Thome, Matthieu Cord, Patrick Perez
A crucial property of KLoS is to be a class-wise divergence measure built from in-distribution samples and to not require OOD training data, in contrast to current second-order uncertainty measures.
no code implementations • 6 May 2019 • Arnaud Dapogny, Matthieu Cord, Patrick Perez
Image completion is the problem of generating whole images from fragments only.
1 code implementation • ICCV 2019 • Senthil Yogamani, Ciaran Hughes, Jonathan Horgan, Ganesh Sistu, Padraig Varley, Derek O'Dea, Michal Uricar, Stefan Milz, Martin Simon, Karl Amende, Christian Witt, Hazem Rashed, Sumanth Chennupati, Sanjaya Nayak, Saquib Mansoor, Xavier Perroton, Patrick Perez
Fisheye cameras are commonly employed for obtaining a large field of view in surveillance, augmented reality and in particular automotive applications.
1 code implementation • CVPR 2019 • Huy V. Vo, Francis Bach, Minsu Cho, Kai Han, Yann Lecun, Patrick Perez, Jean Ponce
Learning with complete or partial supervision is powerful but relies on ever-growing human annotation efforts.
Ranked #2 on Single-object colocalization on Object Discovery
no code implementations • 6 Jan 2019 • Victor Talpaert, Ibrahim Sobh, B Ravi Kiran, Patrick Mannion, Senthil Yogamani, Ahmad El-Sallab, Patrick Perez
Deep Reinforcement Learning (DRL) has become increasingly powerful in recent years, with notable achievements such as Deepmind's AlphaGo.
no code implementations • 17 Apr 2018 • Juan-Manuel Perez-Rua, Tomas Crivelli, Patrick Bouthemy, Patrick Perez
We bypass the need for a tailored loss function on the regression parameters by attaching to our model a differentiable hard-wired decoder corresponding to the polynomial operation at hand.
no code implementations • 27 Mar 2018 • Huy V. Vo, Ngoc Q. K. Duong, Patrick Perez
Scene-agnostic visual inpainting remains very challenging despite progress in patch-based methods.
1 code implementation • 6 Nov 2017 • Erwan Le Merrer, Patrick Perez, Gilles Trédan
The state of the art performance of deep learning models comes at a high cost for companies and institutions, due to the tedious data collection and the heavy processing requirements.
Cryptography and Security
no code implementations • CVPR 2017 • Rafael S. Rezende, Joaquin Zepeda, Jean Ponce, Francis Bach, Patrick Perez
Zepeda and Perez have recently demonstrated the promise of the exemplar SVM (ESVM) as a feature encoder for image retrieval.
no code implementations • CVPR 2016 • Juan-Manuel Perez-Rua, Tomas Crivelli, Patrick Bouthemy, Patrick Perez
With this in mind, we propose a novel approach to occlusion detection where visibility or not of a point in next frame is formulated in terms of visual reconstruction.
no code implementations • CVPR 2014 • Pablo Garrido, Levi Valgaerts, Ole Rehmsen, Thorsten Thormaehlen, Patrick Perez, Christian Theobalt
We propose an image-based, facial reenactment system that replaces the face of an actor in an existing target video with the face of a user from a source video, while preserving the original target performance.
no code implementations • CVPR 2015 • Joaquin Zepeda, Patrick Perez
In this work, we investigate the use of exemplar SVMs (linear SVMs trained with one positive example only and a vast collection of negative examples) as encoders that turn generic image features into new, task-tailored features.
no code implementations • 13 Mar 2015 • Praveen Kulkarni, Joaquin Zepeda, Frederic Jurie, Patrick Perez, Louis Chevallier
A second variant of our approach that includes the fully connected DCNN layers significantly outperforms Fisher vector schemes and performs comparably to DCNN approaches adapted to Pascal VOC 2007, yet at only a small fraction of the training and testing cost.