Handling Noisy Imbalanced Multimodal Data: A Review

Handling Noisy Imbalanced Multimodal Data: A Review

Multimodal fusion aims to integrate information from various modalities to achieve more accurate predictions. Significant progress has been made in multimodal fusion across a wide range of scenarios including autonomous driving and medical diagnosis. However, the reliability of multimodal fusion in low-quality data environments remains largely unexplored. This paper reviews the common challenges and recent … Read more