Introduction to Eccv 2020 Paper Compilation Tum Visual Computing Lab Collaborators
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Eccv 2020 Paper Compilation Tum Visual Computing Lab Collaborators Comprehensive Overview
Eight CVPR NPMs: Neural Parametric Models for 3D Deformable Shapes https://pablopalafox.github.io/npms/ Pablo Palafox, Aljaž Božič, ... Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction https://gafniguy.github.io/4D-Facial-Avatars/ Guy ...
Text2Tex: Text-driven Texture Synthesis via Diffusion Models Dave Zhenyu Chen, Yawar Siddiqui, Hsin-Ying Lee, Sergey ...
Summary & Highlights for Eccv 2020 Paper Compilation Tum Visual Computing Lab Collaborators
- AutoRF: Learning 3D Object Radiance Fields from Single View Observations https://sirwyver.github.io/AutoRF/ Norman Müller, ...
- DiffusionAvatars: Deferred Diffusion for High-fidelity 3D Head Avatars Tobias Kirschstein, Simon Giebenhain, Matthias Nießner ...
- Learning Neural Parametric Head Models Simon Giebenhain, Tobias Kirschstein, Markos Georgopoulos, Martin Rünz, Lourdes ...
- Short presentation for the
- Object recognition has seen significant progress in the image domain, with focus primarily on 2D perception. We propose to ...
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