A Deep Multiscale Spatiotemporal Network for Assessing Depression from Facial Dynamics
Author:
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Human-Computer Interaction,Software
Link
http://xplorestaging.ieee.org/ielx7/5165369/5520654/09186792.pdf?arnumber=9186792
Cited by 33 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Depressformer: Leveraging Video Swin Transformer and fine-grained local features for depression scale estimation;Biomedical Signal Processing and Control;2024-10
2. Demystifying Mental Health by Decoding Facial Action Unit Sequences;Big Data and Cognitive Computing;2024-07-09
3. Robust sparse graph regularized nonnegative matrix factorization for automatic depression diagnosis;Biomedical Signal Processing and Control;2024-07
4. DepMSTAT: Multimodal Spatio-Temporal Attentional Transformer for Depression Detection;IEEE Transactions on Knowledge and Data Engineering;2024-07
5. Spatial–Temporal Attention Network for Depression Recognition from facial videos;Expert Systems with Applications;2024-03
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