2 papers
cs.CV2024
Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes
Raphael Lafargue, Yassir Bendou, Bastien Pasdeloup +4
When training data is scarce, it is common to make use of a feature extractor that has been pre-trained on a large base dataset, either by fine-tuning its parameters on the ``targe…
cs.CV2023
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…