Multimodal Sentiment Analysis Comparison Hub
3 papers - avg viability 4.7
Top Papers
- Progressive Representation Learning for Multimodal Sentiment Analysis with Incomplete Modalities(7.0)
A framework for robust multimodal sentiment analysis that effectively handles incomplete data modalities.
- Tri-Subspaces Disentanglement for Multimodal Sentiment Analysis(5.0)
Tri-Subspace Disentanglement framework improves multimodal sentiment analysis by enhancing cross-modal synergies and modality-specific cues.
- Temporal-Spatial Decouple before Act: Disentangled Representation Learning for Multimodal Sentiment Analysis(2.0)
A novel model for improving multimodal sentiment analysis by decoupling temporal and spatial features before alignment.