10 papers · 1 filter
Sparse auto-regressive modeling for scene generation from multi-view images
Thomas Lucas, Maxime Pietrantoni, Philippe Weinzaepfel +4
Generating complete 3D scenes from sparse, unconstrained views is a fundamental challenge in 3D vision which requires reasoning beyond observed content while remaining computationa…
Human Mesh Modeling for Anny Body
Romain Brégier, Guénolé Fiche, Laura Bravo-Sánchez +5
Parametric body models provide the structural basis for many human-centric tasks, yet existing models often rely on costly 3D scans and learned shape spaces that are proprietary an…
DUNE: Distilling a Universal Encoder from Heterogeneous 2D and 3D Teachers
Mert Bulent Sariyildiz, Philippe Weinzaepfel, Thomas Lucas +3
Recent multi-teacher distillation methods have unified the encoders of multiple foundation models into a single encoder, achieving competitive performance on core vision tasks like…
CondiMen: Conditional Multi-Person Mesh Recovery
Brégier Romain, Baradel Fabien, Lucas Thomas +4
Multi-person human mesh recovery (HMR) consists in detecting all individuals in a given input image, and predicting the body shape, pose, and 3D location for each detected person.…
UNIC: Universal Classification Models via Multi-teacher Distillation
Mert Bulent Sariyildiz, Philippe Weinzaepfel, Thomas Lucas +2
Pretrained models have become a commodity and offer strong results on a broad range of tasks. In this work, we focus on classification and seek to learn a unique encoder able to ta…
T2LM: Long-Term 3D Human Motion Generation from Multiple Sentences
Taeryung Lee, Fabien Baradel, Thomas Lucas +2
In this paper, we address the challenging problem of long-term 3D human motion generation. Specifically, we aim to generate a long sequence of smoothly connected actions from a str…