6 papers
Multimodal Functional Maximum Correlation for Emotion Recognition
Deyang Zheng, Tianyi Zhang, Wenming Zheng +1
Emotional states manifest as coordinated yet heterogeneous physiological responses across central and autonomic systems, posing a fundamental challenge for multimodal representatio…
A Hybrid Graph Neural Network for Enhanced EEG-Based Depression Detection
Yiye Wang, Wenming Zheng, Yang Li +1
Graph neural networks (GNNs) are becoming increasingly popular for EEG-based depression detection. However, previous GNN-based methods fail to sufficiently consider the characteris…
MPT: Motion Prompt Tuning for Micro-Expression Recognition
Jiateng Liu, Hengcan Shi, Feng Chen +4
Micro-expression recognition (MER) is crucial in the affective computing field due to its wide application in medical diagnosis, lie detection, and criminal investigation. Despite…
PromptEVC: Controllable Emotional Voice Conversion with Natural Language Prompts
Tianhua Qi, Shiyan Wang, Cheng Lu +4
Controllable emotional voice conversion (EVC) aims to manipulate emotional expressions to increase the diversity of synthesized speech. Existing methods typically rely on predefine…
Emotion Knowledge Enhancement for Vision Large Language Models: A Self-Verification Approach for High-Quality Emotion Instruction Data Generation
Feifan Wang, Tengfei Song, Minggui He +5
Facial emotion perception in the vision large language model (VLLM) is crucial for achieving natural human-machine interaction. However, creating high-quality annotations for both…
Computational Analysis of Stress, Depression and Engagement in Mental Health: A Survey
Puneet Kumar, Alexander Vedernikov, Yuwei Chen +2
Analysis of stress, depression and engagement is less common and more complex than that of frequently discussed emotions such as happiness, sadness, fear and anger. The importance…