1 code implementation • 24 Jun 2020 • Arthur Douillard, Eduardo Valle, Charles Ollion, Thomas Robert, Matthieu Cord
Continual learning aims to learn tasks sequentially, with (often severe) constraints on the storage of old learning samples, without suffering from catastrophic forgetting.
2 code implementations • ECCV 2020 • Arthur Douillard, Matthieu Cord, Charles Ollion, Thomas Robert, Eduardo Valle
Lifelong learning has attracted much attention, but existing works still struggle to fight catastrophic forgetting and accumulate knowledge over long stretches of incremental learning.
1 code implementation • 3 Jun 2019 • Thomas Robert, Nicolas Thome, Matthieu Cord
To effectively separate the information, we propose to use a combination of regular and adversarial classifiers to guide the two branches in specializing for class and attribute information respectively.
no code implementations • ECCV 2018 • Thomas Robert, Nicolas Thome, Matthieu Cord
In this paper, we introduce a new model for leveraging unlabeled data to improve generalization performances of image classifiers: a two-branch encoder-decoder architecture called HybridNet.
Ranked #53 on Image Classification on STL-10
1 code implementation • 14 May 2018 • Michael Blot, Thomas Robert, Nicolas Thome, Matthieu Cord
Regularization is a big issue for training deep neural networks.
no code implementations • 29 Apr 2018 • Michael Blot, Thomas Robert, Nicolas Thome, Matthieu Cord
Regularization is a big issue for training deep neural networks.
no code implementations • ICLR 2018 • Michael Blot, Thomas Robert, Nicolas Thome, Matthieu Cord
Regularization is a big issue for training deep neural networks.
1 code implementation • 18 Oct 2016 • Rémi Cadène, Thomas Robert, Nicolas Thome, Matthieu Cord
Our approach is among the three best to tackle the M2CAI Workflow challenge.