no code implementations • 19 Apr 2024 • Nicolas Ugrinovic, Thomas Lucas, Fabien Baradel, Philippe Weinzaepfel, Gregory Rogez, Francesc Moreno-Noguer
We present a novel method to generate human motion to populate 3D indoor scenes.
1 code implementation • 22 Feb 2024 • Fabien Baradel, Matthieu Armando, Salma Galaaoui, Romain Brégier, Philippe Weinzaepfel, Grégory Rogez, Thomas Lucas
We present Multi-HMR, a strong single-shot model for multi-person 3D human mesh recovery from a single RGB image.
Ranked #1 on 3D Human Pose Estimation on UBody
no code implementations • 15 Nov 2023 • Matthieu Armando, Salma Galaaoui, Fabien Baradel, Thomas Lucas, Vincent Leroy, Romain Brégier, Philippe Weinzaepfel, Grégory Rogez
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 on large datasets.
no code implementations • 19 Sep 2023 • Anilkumar Swamy, Vincent Leroy, Philippe Weinzaepfel, Fabien Baradel, Salma Galaaoui, Romain Bregier, Matthieu Armando, Jean-Sebastien Franco, Gregory Rogez
Recent hand-object interaction datasets show limited real object variability and rely on fitting the MANO parametric model to obtain groundtruth hand shapes.
1 code implementation • 19 Oct 2022 • Thomas Lucas, Fabien Baradel, Philippe Weinzaepfel, Grégory Rogez
The discrete and compressed nature of the latent space allows the GPT-like model to focus on long-range signal, as it removes low-level redundancy in the input signal.
1 code implementation • 22 Aug 2022 • Fabien Baradel, Romain Brégier, Thibault Groueix, Philippe Weinzaepfel, Yannis Kalantidis, Grégory Rogez
It is simple, generic and versatile, as it can be plugged on top of any image-based model to transform it in a video-based model leveraging temporal information.
no code implementations • ICLR 2022 • Steeven Janny, Fabien Baradel, Natalia Neverova, Madiha Nadri, Greg Mori, Christian Wolf
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 signals dominated by appearance, lighting, textures and also spurious correlations in the data.
1 code implementation • 18 Oct 2021 • Fabien Baradel, Thibault Groueix, Philippe Weinzaepfel, Romain Brégier, Yannis Kalantidis, Grégory Rogez
In fact, we show that simply fine-tuning the batch normalization layers of the model is enough to achieve large gains.
Ranked #59 on 3D Human Pose Estimation on 3DPW
1 code implementation • ICLR 2020 • Fabien Baradel, Natalia Neverova, Julien Mille, Greg Mori, Christian Wolf
Understanding causes and effects in mechanical systems is an essential component of reasoning in the physical world.
no code implementations • 13 Jun 2019 • Chen Sun, Fabien Baradel, Kevin Murphy, Cordelia Schmid
This paper proposes a self-supervised learning approach for video features that results in significantly improved performance on downstream tasks (such as video classification, captioning and segmentation) compared to existing methods.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
1 code implementation • ECCV 2018 • Fabien Baradel, Natalia Neverova, Christian Wolf, Julien Mille, Greg Mori
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 features related to the global context.
Ranked #1 on Semantic Object Interaction Classification on VLOG
1 code implementation • CVPR 2018 • Fabien Baradel, Christian Wolf, Julien Mille, Graham W. Taylor
No spatial coherence is forced on the glimpse locations, which gives the module liberty to explore different points at each frame and better optimize the process of scrutinizing visual information.
Ranked #19 on Skeleton Based Action Recognition on N-UCLA
no code implementations • 20 Dec 2017 • 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 the most discriminative moments in an action.
no code implementations • 29 Mar 2017 • Fabien Baradel, Christian Wolf, Julien Mille
We show that it is of high interest to shift the attention to different hands at different time steps depending on the activity itself.