Toward Facial Expression Recognition in the Wild via Noise-Tolerant Network-Reference-Cited by-同舟云学术

Toward Facial Expression Recognition in the Wild via Noise-Tolerant Network

Published:2023-05 Issue:5 Volume:33 Page:2033-2047
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Gu Yu¹^ORCID,Yan Huan¹^ORCID,Zhang Xiang¹^ORCID,Wang Yantong¹^ORCID,Ji Yusheng²^ORCID,Ren Fuji³^ORCID

Affiliation:

1. S2AC Laboratory and the Key Laboratory of Knowledge Engineering with Big Data, School of Computer and Information, Hefei University of Technology, Anhui, China

2. National Institute of Informatics, Tokyo, Japan

3. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

Funder

Key Research and Development Plan of Anhui Province

Fundamental Research Fund of Chinese Academy of Medical Sciences

Open Fund of Anhui Province Key Laboratory of Cyberspace Security Situation Awareness and Evaluation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

http://xplorestaging.ieee.org/ielx7/76/10116045/09941139.pdf?arnumber=9941139

Reference63 articles.

1. The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression

2. Efficient Facial Feature Learning with Wide Ensemble-Based Convolutional Neural Networks

3. Convolution by Multiplication: Accelerated Two-Stream Fourier Domain Convolutional Neural Network for Facial Expression Recognition

4. Patch-Gated CNN for Occlusion-aware Facial Expression Recognition

5. Reliable Crowdsourcing and Deep Locality-Preserving Learning for Expression Recognition in the Wild

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