Data Driven 3D Vision - Edmond Boyer

Description

The chair aims at investigating deep learning for 3D artificial vision in order to break some of the limitations in this domain. Applications are especially related to humans and to the ability to capture and analyze their shapes, appearances and motions, for upcoming new media devices, sport and medical applications.

Scientific publications

Lastest publication:

Adaptative Mesh Texture for Multi-View Appearance Modeling,
Matthieu Armando, Jean-Sébastien Franco, Edmond Boyer.
3DV 2019 - 7th International Conference on 3D Vision, Sep 2019, Quebec City, Canada.

Reconstructing Human Body Mesh from Point Clouds by Adversarial GP, Network?Boyao Zhou, Jean-Sébastien Franco, Federica Bogo, Bugra Tekin, Edmond Boyer.
ACCV 2020, Asian Conference on Computer Vision, Kyoto, Japan.