Self-Supervised Learning

Cluster and Predict Latents Patches for Improved Masked Image Modeling
TMLR 2025 - Stable training of dense image representations using a clustering loss on ViT patch tokens.
Timothée Darcet, Federico Baldassarre, Maxime Oquab, Julien Mairal, Piotr Bojanowski
PDF Code
Cluster and Predict Latents Patches for Improved Masked Image Modeling
Variable Rate Allocation for Vector-Quantized Autoencoders
ICASSP 2023 - Control the bit rate allocation of a a PQ-VAE using semantic information from DINO, in collaboration with Meta AI in Paris.
Federico Baldassarre, Alaaeldin El-Nouby, Hervé Jégou
PDF Cite Poster
Variable Rate Allocation for Vector-Quantized Autoencoders
Towards Self-Supervised Learning of Global and Object-Centric Representations
ICLR Workshop 2022 - How to learn object-centric representations using contrastive learning on multi-object datasets?
Federico Baldassarre, Hossein Azizpour
PDF Cite Code Poster DOI
Towards Self-Supervised Learning of Global and Object-Centric Representations