no code implementations • CVPR 2014 • Vagia Tsiminaki, Jean-Sebastien Franco, Edmond Boyer
To this goal we use 2D warps for all viewpoints and all temporal frames and a linear image formation model from texture to image space.
no code implementations • CVPR 2015 • Benjamin Allain, Jean-Sebastien Franco, Edmond Boyer
While numerically plausible, this paradigm ignores the fact that the observed surfaces often delimit volumetric shapes, for which deformations are constrained by the volume inside the shape.
no code implementations • 6 Jan 2016 • Benjamin Allain, Li Wang, Jean-Sebastien Franco, Franck Hetroy, Edmond Boyer
Instead of using the dominant surface-based geometric representation of the capture, which is less suitable for volumetric effects, our pipeline exploits Centroidal Voronoi tessellation decompositions as unified volumetric representation of the real captured actor, which we show can be used seamlessly as a building block for all processing stages, from capture and tracking to virtual physic simulation.
no code implementations • CVPR 2016 • Chun-Hao Huang, Benjamin Allain, Jean-Sebastien Franco, Nassir Navab, Slobodan Ilic, Edmond Boyer
In this paper, we propose a new framework for 3D tracking by detection based on fully volumetric representations.
no code implementations • CVPR 2017 • Adnane Boukhayma, Jean-Sebastien Franco, Edmond Boyer
We address the problem of transferring motion between captured 4D models.
no code implementations • ICCV 2017 • Vincent Leroy, Jean-Sebastien Franco, Edmond Boyer
We consider 4D shape reconstructions in multi-view environments and investigate how to exploit temporal redundancy for precision refinement.
no code implementations • ECCV 2018 • Jinlong Yang, Jean-Sebastien Franco, Franck Hetroy-Wheeler, Stefanie Wuhrer
Recent capture technologies and methods allow not only to retrieve 3D model sequence of moving people in clothing, but also to separate and extract the underlying body geometry, motion component and the clothing as a geometric layer.
no code implementations • ECCV 2018 • Vincent Leroy, Jean-Sebastien Franco, Edmond Boyer
Our results demonstrate this ability, showing that a CNN, trained on a standard static dataset, can help recover surface details on dynamic scenes that are not perceived by traditional 2D feature based methods.
no code implementations • ICCV 2019 • Valentin Gabeur, Jean-Sebastien Franco, Xavier Martin, Cordelia Schmid, Gregory Rogez
In this paper, we tackle the problem of 3D human shape estimation from single RGB images.
no code implementations • 7 Jun 2021 • Mathieu Marsot, Stefanie Wuhrer, Jean-Sebastien Franco, Stephane Durocher
We propose a framework to learn a structured latent space to represent 4D human body motion, where each latent vector encodes a full motion of the whole 3D human shape.
no code implementations • 27 Jun 2022 • Mathieu Marsot, Stefanie Wuhrer, Jean-Sebastien Franco, Anne Hélène Olivier
We propose a new representation of human body motion which encodes a full motion in a sequence of latent motion primitives.
no code implementations • 12 Jun 2023 • Matthieu Armando, Laurence Boissieux, Edmond Boyer, Jean-Sebastien Franco, Martin Humenberger, Christophe Legras, Vincent Leroy, Mathieu Marsot, Julien Pansiot, Sergi Pujades, Rim Rekik, Gregory Rogez, Anilkumar Swamy, Stefanie Wuhrer
This work presents 4DHumanOutfit, a new dataset of densely sampled spatio-temporal 4D human motion data of different actors, outfits and motions.
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.