Fast and Light Manifold CNN based 3D Facial Expression Recognition across Pose Variations-Reference-Cited by-同舟云学术

Fast and Light Manifold CNN based 3D Facial Expression Recognition across Pose Variations

Published:2018-10-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 26th ACM international conference on Multimedia
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Author:

Chen Zhixing¹,Huang Di¹,Wang Yunhong¹,Chen Liming²

Affiliation:

1. Beihang University, Beijing, China

2. Beihang University; LIRIS, Ecole Centrale de Lyon, Beijing, China

Funder

The Microsoft Research Asia Collaborative Program

The National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3240508.3240568

Reference47 articles.

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3. Davide Boscaini Jonathan Masci Emanuele Rodolà and Michael M. Bronstein. 2016. Learning shape correspondence with anisotropic convolutional neural networks. In Advances in Neural Information Processing Systems. 3189--3197. Davide Boscaini Jonathan Masci Emanuele Rodolà and Michael M. Bronstein. 2016. Learning shape correspondence with anisotropic convolutional neural networks. In Advances in Neural Information Processing Systems. 3189--3197.

4. Michaël Defferrard Xavier Bresson and Pierre Vandergheynst. 2016. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. In Advances in Neural Information Processing Systems. 3837--3845. Michaël Defferrard Xavier Bresson and Pierre Vandergheynst. 2016. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering. In Advances in Neural Information Processing Systems. 3837--3845.

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