113 citations · 263 across the 30 of their papers we have counts for
5 papers · 1 filter
On the inductive biases of deep domain adaptation
Rodrigue Siry, Louis Hémadou, Loïc Simon +1
Domain alignment is currently the most prevalent solution to unsupervised domain-adaptation tasks and are often being presented as minimizers of some theoretical upper-bounds on ri…
Towards a General Model of Knowledge for Facial Analysis by Multi-Source Transfer Learning
Valentin Vielzeuf, Alexis Lechervy, Stéphane Pateux +1
This paper proposes a step toward obtaining general models of knowledge for facial analysis, by addressing the question of multi-source transfer learning. More precisely, the propo…
MFAS: Multimodal Fusion Architecture Search
Juan-Manuel Pérez-Rúa, Valentin Vielzeuf, Stéphane Pateux +2
We tackle the problem of finding good architectures for multimodal classification problems. We propose a novel and generic search space that spans a large number of possible fusion…
Detecting Overfitting of Deep Generative Networks via Latent Recovery
Ryan Webster, Julien Rabin, Loic Simon +1
State of the art deep generative networks are capable of producing images with such incredible realism that they can be suspected of memorizing training images. It is why it is not…
Hard Negative Mining for Metric Learning Based Zero-Shot Classification
Maxime Bucher, Stéphane Herbin, Frédéric Jurie
Zero-Shot learning has been shown to be an efficient strategy for domain adaptation. In this context, this paper builds on the recent work of Bucher et al. [1], which proposed an a…