Cargando…
Micro Expression Recognition via Dual-Stream Spatiotemporal Attention Network
Microexpression can manifest the real mood of humans, which has been widely concerned in clinical diagnosis and depression analysis. To solve the problem of missing discriminative spatiotemporal features in a small data set caused by the short duration and subtle movement changes of microexpression,...
Autores principales: | Wang, Yan, Huang, Yikun, Liu, Can, Gu, Xiaoying, Yang, Dandan, Wang, Shuopeng, Zhang, Bo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8387165/ https://www.ncbi.nlm.nih.gov/pubmed/34457221 http://dx.doi.org/10.1155/2021/7799100 |
Ejemplares similares
-
Dual-ATME: Dual-Branch Attention Network for Micro-Expression Recognition
por: Zhou, Haoliang, et al.
Publicado: (2023) -
Dual Memory LSTM with Dual Attention Neural Network for Spatiotemporal Prediction
por: Li, Teng, et al.
Publicado: (2021) -
Two-Stream Attention Network for Pain Recognition from Video Sequences
por: Thiam, Patrick, et al.
Publicado: (2020) -
Denoising Method Based on Salient Region Recognition for the Spatiotemporal Event Stream
por: Tang, Sichao, et al.
Publicado: (2023) -
Pathological-Gait Recognition Using Spatiotemporal Graph Convolutional Networks and Attention Model
por: Kim, Jungi, et al.
Publicado: (2022)