17 citations · 30 across the 8 of their papers we have counts for
14 papers
Speech Emotion Recognition via an Attentive Time-Frequency Neural Network
Cheng Lu, Wenming Zheng, Hailun Lian +4
Spectrogram is commonly used as the input feature of deep neural networks to learn the high(er)-level time-frequency pattern of speech signal for speech emotion recognition (SER).…
SDFE-LV: A Large-Scale, Multi-Source, and Unconstrained Database for Spotting Dynamic Facial Expressions in Long Videos
Xiaolin Xu, Yuan Zong, Wenming Zheng +4
In this paper, we present a large-scale, multi-source, and unconstrained database called SDFE-LV for spotting the onset and offset frames of a complete dynamic facial expression fr…
GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion Recognition
Yang Li, Ji Chen, Fu Li +7
Previous electroencephalogram (EEG) emotion recognition relies on single-task learning, which may lead to overfitting and learned emotion features lacking generalization. In this p…
Region attention and graph embedding network for occlusion objective class-based micro-expression recognition
Qirong Mao, Ling Zhou, Wenming Zheng +2
Micro-expression recognition (\textbf{MER}) has attracted lots of researchers' attention in a decade. However, occlusion will occur for MER in real-world scenarios. This paper deep…
SMA-STN: Segmented Movement-Attending Spatiotemporal Network forMicro-Expression Recognition
Jiateng Liu, Wenming Zheng, Yuan Zong
Correctly perceiving micro-expression is difficult since micro-expression is an involuntary, repressed, and subtle facial expression, and efficiently revealing the subtle movement…
A Novel Transferability Attention Neural Network Model for EEG Emotion Recognition
Yang Li, Boxun Fu, Fu Li +2
The existed methods for electroencephalograph (EEG) emotion recognition always train the models based on all the EEG samples indistinguishably. However, some of the source (trainin…