5 citations · 12 across the 5 of their papers we have counts for
5 papers
OCTET: Object-aware Counterfactual Explanations
Mehdi Zemni, Mickaël Chen, Éloi Zablocki +3
Nowadays, deep vision models are being widely deployed in safety-critical applications, e.g., autonomous driving, and explainability of such models is becoming a pressing concern.…
Take One Gram of Neural Features, Get Enhanced Group Robustness
Simon Roburin, Charles Corbière, Gilles Puy +4
Predictive performance of machine learning models trained with empirical risk minimization (ERM) can degrade considerably under distribution shifts. The presence of spurious correl…
Self-supervised learning with rotation-invariant kernels
Léon Zheng, Gilles Puy, Elisa Riccietti +2
We introduce a regularization loss based on kernel mean embeddings with rotation-invariant kernels on the hypersphere (also known as dot-product kernels) for self-supervised learni…
Active Learning Strategies for Weakly-supervised Object Detection
Huy V. Vo, Oriane Siméoni, Spyros Gidaris +3
Object detectors trained with weak annotations are affordable alternatives to fully-supervised counterparts. However, there is still a significant performance gap between them. We…
LaRa: Latents and Rays for Multi-Camera Bird's-Eye-View Semantic Segmentation
Florent Bartoccioni, Éloi Zablocki, Andrei Bursuc +3
Recent works in autonomous driving have widely adopted the bird's-eye-view (BEV) semantic map as an intermediate representation of the world. Online prediction of these BEV maps in…