Researcher, CEA
1 paper at NeurIPS 2025
We introduce CaMiT, a large-scale, time-aware dataset of 5.9M car samples (labeled and unlabeled) from 2005–2023, enabling research on temporal shift modeling in fine-grained classification, continual learning, and time-aware image generation.