4 papers
Revisiting Human-in-the-Loop Object Retrieval with Pre-Trained Vision Transformers
Kawtar Zaher, Olivier Buisson, Alexis Joly
Building on existing approaches, we revisit Human-in-the-Loop Object Retrieval, a task that consists of iteratively retrieving images containing objects of a class-of-interest, spe…
Positive-First Most Ambiguous: A Simple Active Learning Criterion for Interactive Retrieval of Rare Categories
Kawtar Zaher, Olivier Buisson, Alexis Joly
Real-world fine-grained visual retrieval often requires discovering a rare concept from large unlabeled collections with minimal supervision. This is especially critical in biodive…
Self-Supervised Learning as Discrete Communication
Kawtar Zaher, Ilyass Moummad, Olivier Buisson +1
Most self-supervised learning (SSL) methods learn continuous visual representations by aligning different views of the same input, offering limited control over how information is…
How does the degree of novelty impacts semi-supervised representation learning for novel class retrieval?
Quentin Leroy, Olivier Buisson, Alexis Joly
Supervised representation learning with deep networks tends to overfit the training classes and the generalization to novel classes is a challenging question. It is common to evalu…