8 citations · 36 across the 25 of their papers we have counts for
3 papers · 1 filter
Inferring Latent Class Statistics from Text for Robust Visual Few-Shot Learning
Yassir Bendou, Vincent Gripon, Bastien Pasdeloup +4
In the realm of few-shot learning, foundation models like CLIP have proven effective but exhibit limitations in cross-domain robustness especially in few-shot settings. Recent work…
A Strong and Simple Deep Learning Baseline for BCI MI Decoding
Yassine El Ouahidi, Vincent Gripon, Bastien Pasdeloup +3
We propose EEG-SimpleConv, a straightforward 1D convolutional neural network for Motor Imagery decoding in BCI. Our main motivation is to propose a simple and performing baseline t…
Disambiguation of One-Shot Visual Classification Tasks: A Simplex-Based Approach
Yassir Bendou, Lucas Drumetz, Vincent Gripon +2
The field of visual few-shot classification aims at transferring the state-of-the-art performance of deep learning visual systems onto tasks where only a very limited number of tra…