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