2 citations · 2 across the 2 of their papers we have counts for
7 papers
Decoupled Hierarchical Distillation for Multimodal Emotion Recognition
Yong Li, Yuanzhi Wang, Yi Ding +3
Human multimodal emotion recognition (MER) seeks to infer human emotions by integrating information from language, visual, and acoustic modalities. Although existing MER approaches…
LEAF: Language-EEG Aligned Foundation Model for Brain-Computer Interfaces
Muyun Jiang, Shuailei Zhang, Zhenjie Yang +9
Recent advances in electroencephalography (EEG) foundation models, which capture transferable EEG representations, have greatly accelerated the development of brain-computer interf…
Decoding Covert Speech from EEG Using a Functional Areas Spatio-Temporal Transformer
Muyun Jiang, Yi Ding, Wei Zhang +14
Covert speech involves imagining speaking without audible sound or any movements. Decoding covert speech from electroencephalogram (EEG) is challenging due to a limited understandi…
Towards Robust Multimodal Physiological Foundation Models: Handling Arbitrary Missing Modalities
Wei-Bang Jiang, Xi Fu, Yi Ding +1
Multimodal physiological signals, such as EEG, ECG, EOG, and EMG, are crucial for healthcare and brain-computer interfaces. While existing methods rely on specialized architectures…
Decoupled Doubly Contrastive Learning for Cross Domain Facial Action Unit Detection
Yong Li, Menglin Liu, Zhen Cui +5
Despite the impressive performance of current vision-based facial action unit (AU) detection approaches, they are heavily susceptible to the variations across different domains and…
Beyond Overfitting: Doubly Adaptive Dropout for Generalizable AU Detection
Yong Li, Yi Ren, Xuesong Niu +3
Facial Action Units (AUs) are essential for conveying psychological states and emotional expressions. While automatic AU detection systems leveraging deep learning have progressed,…