Feature Representation Learning with Adaptive Displacement Generation and Transformer Fusion for Micro-Expression Recognition-Reference-Cited by-同舟云学术

Feature Representation Learning with Adaptive Displacement Generation and Transformer Fusion for Micro-Expression Recognition

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Zhai Zhijun¹,Zhao Jianhui¹,Long Chengjiang²,Xu Wenju³,He Shuangjiang⁴,Zhao Huijuan⁴

Affiliation:

1. School of Computer Science, Wuhan University,Wuhan,Hubei,China

2. Meta Reality Labs,Burlingame,CA,USA

3. InnoPeak Technology Inc,OPPO US Research Center,Palo Alto,CA,USA

4. FiberHome Telecommunication Technologies Co., Ltd,Wuhan,Hubei,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203585.pdf?arnumber=10203585

Reference53 articles.

1. Transformer in transformer;han;proceedings of the 31st Conference on Neural Information Processing Systems (NIPS),0

2. Merastc: Micro-expression recognition using effective feature encodings and 2d convolutional neural network;gupta;IEEE Transactions on Affective Computing,2021

3. Dual-stream Shallow Networks for Facial Micro-expression Recognition

4. Long Short-Term Memory

5. Towards a practical lipreading system

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