7 papers
PoseGPT: Quantization-based 3D Human Motion Generation and Forecasting
Thomas Lucas, Fabien Baradel, Philippe Weinzaepfel +1
We address the problem of action-conditioned generation of human motion sequences. Existing work falls into two categories: forecast models conditioned on observed past motions, or…
Leveraging MoCap Data for Human Mesh Recovery
Fabien Baradel, Thibault Groueix, Philippe Weinzaepfel +3
Training state-of-the-art models for human body pose and shape recovery from images or videos requires datasets with corresponding annotations that are really hard and expensive to…
CoPhy: Counterfactual Learning of Physical Dynamics
Fabien Baradel, Natalia Neverova, Julien Mille +2
Understanding causes and effects in mechanical systems is an essential component of reasoning in the physical world. This work poses a new problem of counterfactual learning of obj…
Learning Video Representations using Contrastive Bidirectional Transformer
Chen Sun, Fabien Baradel, Kevin Murphy +1
This paper proposes a self-supervised learning approach for video features that results in significantly improved performance on downstream tasks (such as video classification, cap…
Object Level Visual Reasoning in Videos
Fabien Baradel, Natalia Neverova, Christian Wolf +2
Human activity recognition is typically addressed by detecting key concepts like global and local motion, features related to object classes present in the scene, as well as featur…
Glimpse Clouds: Human Activity Recognition from Unstructured Feature Points
Fabien Baradel, Christian Wolf, Julien Mille +1
We propose a method for human activity recognition from RGB data that does not rely on any pose information during test time and does not explicitly calculate pose information inte…