Learning a 3D Morphable Face Reflectance Model from Low-Cost Data

Author:

Han Yuxuan1,Wang Zhibo2,Xu Feng1

Affiliation:

1. School of Software and BNRist, Tsinghua University

2. SenseTime Research

Funder

Beijing Natural Science Foundation

NSFC

Tsinghua University

Beijing Municipal Education Commission

Publisher

IEEE

Reference70 articles.

1. Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning

2. Neural voice puppetry: Audio-driven facial reenactment;thies;European Conference on Computer Vision,2020

3. Mofa: Model-based deep convolutional face autoencoder for unsupervised monocular reconstruction;tewari;Proceedings of the IEEE International Conference on Computer Vision Workshops,0

4. S2f2: Self-supervised high fidelity face reconstruction from monocular image;dib;ArXiv Preprint,2022

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1. Self-supervised learning for fine-grained monocular 3D face reconstruction in the wild;Multimedia Systems;2024-08

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3. SR-VFA: Accurate Self-Refined Face Alignment in Videos;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

4. A Deeper Analysis of Volumetric Relightable Faces;International Journal of Computer Vision;2023-10-31

5. NEW SURFACE REFLECTANCE MODEL WITH THE COMBINATION OF TWO CUBIC FUNCTIONS USAGE;Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska;2023-09-30

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