A self-attention-based fusion framework for facial expression recognition in wavelet domain
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-023-03168-3.pdf
Reference53 articles.
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2. Li, T.H.S., Kuo, P.H., Tsai, T.N., Luan, P.C.: CNN and LSTM based facial expression analysis model for a humanoid robot. IEEE Access 7, 93998–94011 (2019)
3. Wang, K., Peng, X., Yang, J., Meng, D., Qiao, Y.: Region attention networks for pose and occlusion robust facial expression recognition. IEEE Trans. Image Process. 29, 4057–4069 (2020)
4. Li, J., Jin, K., Zhou, D., Kubota, N., Ju, Z.: Attention mechanism-based CNN for facial expression recognition. Neurocomputing 411, 340–350 (2020)
5. Zou, W., Zhang, D., Lee, D.J.: A new multi-feature fusion based convolutional neural network for facial expression recognition. Appl. Intell. 52(3), 2918–2929 (2022)
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1. Recognizing facial expressions based on pyramid multi-head grid and spatial attention network;Computer Vision and Image Understanding;2024-07
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