Frugal learning

Collecting diverse enough data, and annotating it precisely, is complex, costly and time-consuming. To reduce dramatically these needs, we explore various alternatives to fully-supervised learning, e.g, training that is unsupervised (as rOSD at ECCCV’20), self-supervised (as BoWNet at CVPR’20), semi-supervised, active, zero-shot (as ZS3 at NeurIPS’19) or few-shot. We also investigate training with fully-synthetic data (in combination with unsupervised domain adaptation) and with GAN-augmented data (as Semantic Palette at CVPR’21).

Publications

Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data

Corentin Sautier, Gilles Puy, Spyros Gidaris, Alexandre Boulch, Andrei Bursuc, and Renaud Marlet
Computer Vision and Pattern Recognition (CVPR), 2022


CSG0: Continual Urban Scene Generation with Zero Forgetting

Himalaya Jain (*), Tuan-Hung Vu (*), Patrick Pérez and Matthieu Cord (* equal contrib.)
Computer Vision and Pattern Recognition (CVPR) Workshop, 2022


Large-Scale Unsupervised Object Discovery

Huy V. Vo, Elena Sizikova, Cordelia Schmid, Patrick Pérez and Jean Ponce
Advances in Neural Information Processing Systems (NeurIPS), 2021


Handling new target classes in semantic segmentation with domain adaptation

Maxime Bucher, Tuan-Hung Vu, Matthieu Cord, and Patrick Pérez
Computer Vision and Image Understanding (CVIU), 2021


Localizing Objects with Self-Supervised Transformers and no Labels

Oriane Siméoni, Gilles Puy, Huy V. Vo, Simon Roburin, Spyros Gidaris, Andrei Bursuc, Patrick Pérez, Renaud Marlet, Jean Ponce
British Machine Vision Conference (BMVC), 2021


Generative Zero-Shot Learning for Semantic Segmentation of 3D Point Clouds

Bjoern Michele, Alexandre Boulch, Gilles Puy, Maxime Bucher, and Renaud Marlet
International Conference on 3D Vision (3DV), 2021


Online Bag-of-Visual-Words Generation for Unsupervised Representation Learning

Spyros Gidaris, Andrei Bursuc, Gilles Puy, Nikos Komodakis, Patrick Pérez, and Matthieu Cord
Computer Vision and Pattern Recognition (CVPR), 2021


Semantic Palette: Guiding Scene Generation with Class Proportions

Guillaume Le Moing, Tuan-Hung Vu, Himalaya Jain, Patrick Pérez and Matthieu Cord
Computer Vision and Pattern Recognition (CVPR), 2021


Artificial Dummies for Urban Dataset Augmentation

Antonín Vobecký, David Hurych, Michal Uřičář, Patrick Pérez, and Josef Šivic
AAAI Conference on Artificial Intelligence (AAAI), 2021


Toward Unsupervised, Multi-Object Discovery in Large-Scale Image Collections

Huy V. Vo, Patrick Pérez and Jean Ponce
European Conference on Computer Vision (ECCV), 2020


Learning Representations by Predicting Bags of Visual Words

Spyros Gidaris, Andrei Bursuc, Nikos Komodakis, Patrick Pérez, and Matthieu Cord
Computer Vision and Pattern Recognition (CVPR), 2020


This dataset does not exist: training models from generated images

Victor Besnier, Himalaya Jain, Andrei Bursuc, Matthieu Cord, and Patrick Pérez
International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020


Zero-Shot Semantic Segmentation

Maxime Bucher, Tuan-Hung Vu, Matthieu Cord, and Patrick Pérez
Neural Information Processing Systems (NeurIPS), 2019


Boosting Few-Shot Visual Learning With Self-Supervision

Spyros Gidaris, Andrei Bursuc, Nikos Komodakis, Patrick Pérez, and Matthieu Cord
International Conference on Computer Vision (ICCV), 2019


Unsupervised Image Matching and Object Discovery as Optimization

Huy V. Vo, Francis Bach, Minsu Cho, Kai Han, Yann Lecun, Patrick Pérez and Jean Ponce
Computer Vision and Pattern Recognition (CVPR), 2019