224 citations · 421 across the 16 of their papers we have counts for
19 papers
Multi-HMR 2: Multi-Person Camera-Centric Human Detection, Mesh Recovery and Tracking
Guénolé Fiche, Philippe Weinzaepfel, Romain Brégier +1
Most advances in human mesh recovery (HMR) have focused on pelvis-centered recovery, overlooking metric 3D localization and detection accuracy in the camera coordinate system - two…
Anny-Fit: All-Age Human Mesh Recovery
Laura Bravo-Sánchez, Matthieu Armando, Romain Brégier +3
Recovering 3D human pose and shape from a single image remains a cornerstone of human-centric vision, yet most methods assume adult subjects and optimize each person independently.…
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…
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.…
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…
Cross-view and Cross-pose Completion for 3D Human Understanding
Matthieu Armando, Salma Galaaoui, Fabien Baradel +5
Human perception and understanding is a major domain of computer vision which, like many other vision subdomains recently, stands to gain from the use of large models pre-trained o…
SHOWMe: Benchmarking Object-agnostic Hand-Object 3D Reconstruction
Anilkumar Swamy, Vincent Leroy, Philippe Weinzaepfel +6
Recent hand-object interaction datasets show limited real object variability and rely on fitting the MANO parametric model to obtain groundtruth hand shapes. To go beyond these lim…
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…
PoseBERT: A Generic Transformer Module for Temporal 3D Human Modeling
Fabien Baradel, Romain Brégier, Thibault Groueix +3
Training state-of-the-art models for human pose estimation in videos requires datasets with annotations that are really hard and expensive to obtain. Although transformers have bee…
Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space
Steeven Janny, Fabien Baradel, Natalia Neverova +3
Learning causal relationships in high-dimensional data (images, videos) is a hard task, as they are often defined on low dimensional manifolds and must be extracted from complex si…
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…
Human Action Recognition: Pose-based Attention draws focus to Hands
Fabien Baradel, Christian Wolf, Julien Mille
We propose a new spatio-temporal attention based mechanism for human action recognition able to automatically attend to the hands most involved into the studied action and detect t…
Pose-conditioned Spatio-Temporal Attention for Human Action Recognition
Fabien Baradel, Christian Wolf, Julien Mille
We address human action recognition from multi-modal video data involving articulated pose and RGB frames and propose a two-stream approach. The pose stream is processed with a con…