5 papers · 1 filter
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…
Purposer: Putting Human Motion Generation in Context
Nicolas Ugrinovic, Thomas Lucas, Fabien Baradel +3
We present a novel method to generate human motion to populate 3D indoor scenes. It can be controlled with various combinations of conditioning signals such as a path in a scene, t…
Multi-HMR: Multi-Person Whole-Body Human Mesh Recovery in a Single Shot
Fabien Baradel, Matthieu Armando, Salma Galaaoui +4
We present Multi-HMR, a strong sigle-shot model for multi-person 3D human mesh recovery from a single RGB image. Predictions encompass the whole body, i.e., including hands and fac…