Data Driven 3D Vision

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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.

SELECTED LIST OF PUBLICATIONS

  • Vincent Leroy, Jean-Sébastien Franco, Edmond Boyer. Volume Sweeping: Learning Photoconsistency for Multi-View Shape Reconstruction. International Journal of Computer Vision, Springer Verlag, 2021, 129, pp.284-299.

  • Jean Basset, Adnane Boukhayma, Stefanie Wuhrer, Franck Multon, Edmond Boyer. Neural Human Deformation Transfer. International conference on 3D Vision, Dec 2021, London, United Kingdom

  • Pierre Zins, Yuanlu Xu, Edmond Boyer, Stefanie Wuhrer, Tony Tung. Data-Driven 3D Reconstruction of Dressed Humans From Sparse Views. 3DV 2021 - International Conference on 3D Vision, Dec 2021, London, United Kingdom.

  • 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.
Published on  January 11, 2024
Updated on January 11, 2024