5 papers
Asynchronous Multimodal Video Sequence Fusion via Learning Modality-Exclusive and -Agnostic Representations
Dingkang Yang, Mingcheng Li, Linhao Qu +4
Understanding human intentions (e.g., emotions) from videos has received considerable attention recently. Video streams generally constitute a blend of temporal data stemming from…
Towards Context-Aware Emotion Recognition Debiasing from a Causal Demystification Perspective via De-confounded Training
Dingkang Yang, Kun Yang, Haopeng Kuang +3
Understanding emotions from diverse contexts has received widespread attention in computer vision communities. The core philosophy of Context-Aware Emotion Recognition (CAER) is to…
Towards Multimodal Sentiment Analysis Debiasing via Bias Purification
Dingkang Yang, Mingcheng Li, Dongling Xiao +7
Multimodal Sentiment Analysis (MSA) aims to understand human intentions by integrating emotion-related clues from diverse modalities, such as visual, language, and audio. Unfortuna…
Correlation-Decoupled Knowledge Distillation for Multimodal Sentiment Analysis with Incomplete Modalities
Mingcheng Li, Dingkang Yang, Xiao Zhao +7
Multimodal sentiment analysis (MSA) aims to understand human sentiment through multimodal data. Most MSA efforts are based on the assumption of modality completeness. However, in r…
Robust Emotion Recognition in Context Debiasing
Dingkang Yang, Kun Yang, Mingcheng Li +3
Context-aware emotion recognition (CAER) has recently boosted the practical applications of affective computing techniques in unconstrained environments. Mainstream CAER methods in…