no code implementations • 4 May 2023 • Connor Z. Lin, Koki Nagano, Jan Kautz, Eric R. Chan, Umar Iqbal, Leonidas Guibas, Gordon Wetzstein, Sameh Khamis
To tackle this problem, we propose a novel method for constructing implicit 3D morphable face models that are both generalizable and intuitive for editing.
no code implementations • 18 Jul 2022 • Connor Z. Lin, Niloy J. Mitra, Gordon Wetzstein, Leonidas Guibas, Paul Guerrero
Neural representations are popular for representing shapes, as they can be learned form sensor data and used for data cleanup, model completion, shape editing, and shape synthesis.
no code implementations • 25 Mar 2022 • Connor Z. Lin, David B. Lindell, Eric R. Chan, Gordon Wetzstein
Portrait image animation enables the post-capture adjustment of these attributes from a single image while maintaining a photorealistic reconstruction of the subject's likeness or identity.
2 code implementations • CVPR 2022 • Eric R. Chan, Connor Z. Lin, Matthew A. Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas Guibas, Jonathan Tremblay, Sameh Khamis, Tero Karras, Gordon Wetzstein
Unsupervised generation of high-quality multi-view-consistent images and 3D shapes using only collections of single-view 2D photographs has been a long-standing challenge.
1 code implementation • 6 May 2021 • Julien N. P. Martel, David B. Lindell, Connor Z. Lin, Eric R. Chan, Marco Monteiro, Gordon Wetzstein
Here, we introduce a new hybrid implicit-explicit network architecture and training strategy that adaptively allocates resources during training and inference based on the local complexity of a signal of interest.