no code implementations • 22 Apr 2024 • Safa C. Medin, Gengyan Li, Ruofei Du, Stephan Garbin, Philip Davidson, Gregory W. Wornell, Thabo Beeler, Abhimitra Meka
3D rendering of dynamic face captures is a challenging problem, and it demands improvements on several fronts$\unicode{x2014}$photorealism, efficiency, compatibility, and configurability.
no code implementations • ICCV 2023 • Marcel C. Bühler, Kripasindhu Sarkar, Tanmay Shah, Gengyan Li, Daoye Wang, Leonhard Helminger, Sergio Orts-Escolano, Dmitry Lagun, Otmar Hilliges, Thabo Beeler, Abhimitra Meka
NeRFs have enabled highly realistic synthesis of human faces including complex appearance and reflectance effects of hair and skin.
1 code implementation • CVPR 2023 • Alessandro Ruzzi, Xiangwei Shi, Xi Wang, Gengyan Li, Shalini De Mello, Hyung Jin Chang, Xucong Zhang, Otmar Hilliges
We propose GazeNeRF, a 3D-aware method for the task of gaze redirection.
no code implementations • 16 Jun 2022 • Gengyan Li, Abhimitra Meka, Franziska Müller, Marcel C. Bühler, Otmar Hilliges, Thabo Beeler
The challenge of synthesizing eyes is multifold as it requires 1) appropriate representations for the various components of the eye and the periocular region for coherent viewpoint synthesis, capable of representing diffuse, refractive and highly reflective surfaces, 2) disentangling skin and eye appearance from environmental illumination such that it may be rendered under novel lighting conditions, and 3) capturing eyeball motion and the deformation of the surrounding skin to enable re-gazing.
1 code implementation • ICCV 2021 • Marcel C. Bühler, Abhimitra Meka, Gengyan Li, Thabo Beeler, Otmar Hilliges
In this paper, we propose VariTex - to the best of our knowledge the first method that learns a variational latent feature space of neural face textures, which allows sampling of novel identities.