Unsupervised Multi-object Segmentation Using Attention and Soft-argmax. - Bruno Sauvalle; Arnaud de La Fortelle (CoRR, 2022)

Fast and Accurate Background Reconstruction Using Background Bootstrapping. - Bruno Sauvalle; Arnaud de La Fortelle (J. Imaging, 2022)

Autoencoder-based background reconstruction and foreground segmentation with background noise estimation. - Bruno Sauvalle; Arnaud de La Fortelle (WACV, 2023)

Self-supervised learning of object-centric representations with multi-object detection and segmentation. (Apprentissage auto-supervisé de représentations centrées sur les objets avec détection et segmentation multi-objets). - Bruno Sauvalle (2023)

Hybrid diffusion models: combining supervised and generative pretraining for label-efficient fine-tuning of segmentation models. - Bruno Sauvalle; Mathieu Salzmann (CoRR, 2024)