Sparse to Dense Dynamic 3D Facial Expression Generation-Reference-Cited by-同舟云学术

Sparse to Dense Dynamic 3D Facial Expression Generation

Published:2022-06 Issue: Volume: Page:
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Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Otberdout Naima¹,Ferrari Claudio²,Daoudi Mohamed³,Berretti Stefano⁴,Del Bimbo Alberto⁴

Affiliation:

1. Univ. Lille,CNRS, Inria, Centrale Lille, UMR 9189 CRIStAL,Lille,France,F-59000

2. University of Parma,Deparment of Architecture and Engineering,Italy

3. Institut Mines-Télécom, Univ. Lille, Centre for Digital Systems,IMT Nord Europe,France

4. Media Integration ad Communication Center University of Florence,Italy

Publisher

IEEE

Link

Reference46 articles.

1. Learning to generate customized dynamic 3D facial expressions;potamias;European Conf on Computer Vision (ECCV),0

4. A simple approach to intrinsic correspondence learning on unstructured 3D meshes;lim;Eur Conf Comput Vision (ECCV),2018

5. Learning a model of facial shape and expression from 4D scans;li;ACM Trans on Graphics (Proc of SIGGRAPH),0

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5. 3D Facial Expression Generator Based on Transformer VAE;2023 IEEE International Conference on Image Processing (ICIP);2023-10-08