Cvpr 2023 Implicit 3d Human

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Paper: https://arxiv.org/abs/2304.09502 Code: https://github.com/DCVL-

Realistic face rendering from multi-view images is beneficial to various computer vision and graphics applications. Due to the ...

Modeling non-Lambertian effects such as facial specularity leads to a more realistic

Website: https://xmeng525.github.io/xiaoxumeng.github.io/projects/cvpr23_neat Abstract: Recent progress in neural

CVPR 2023

Project page: https://gerwang.github.io/shadowneus/ Abstract: By supervising camera rays between a scene and multi-view image ...

Project: https://dazinovic.github.io/polface/ We propose a novel method for high-quality facial texture reconstruction from RGB ...

Learning Neural Parametric Head Models Simon Giebenhain, Tobias Kirschstein, Markos Georgopoulos, Martin Rünz, Lourdes ...

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Project: https://suezjiang.github.io/humangen/ Arxiv: https://arxiv.org/abs/2212.05321 Recent years have witnessed the ...

project page: https://lyx0208.github.io/3dSwap/

Introduction of 'Learning

If you have any copyright issues on video, please send us an email at khawar512@gmail.com 0:00 Introduction 0:10 Problem ...

Technical introductory video of paper: Learning Neural Volumetric Representations of Dynamic

Our project website: https://sites.google.com/view/nemo-neural-motion-field.

We present

CVPR 2023 Controllable 3D Shape Generation

[CVPR 2023] TAPS3D: Text-Guided 3D Textured Shape Generation from Pseudo Supervision

Abstract We introduce a method that can learn to predict scene-level