Multimodal Fusion on Low-quality Data: A Comprehensive Survey

arXiv:2404.18947v1 Announce Type: new
Abstract: Multimodal fusion focuses on integrating information from multiple modalities with the goal of more accurate prediction, which has achieved remarkable progress in a wide range of scenarios, including autonomous driving and medical diagnosis. However, the reliability of multimodal fusion remains largely unexplored especially under low-quality data settings. This paper surveys the common challenges and recent advances of multimodal fusion in the wild and presents them in a comprehensive taxonomy. From a data-centric view, we identify …

abstract arxiv autonomous autonomous driving cs.ai cs.lg data diagnosis driving fusion however information low medical multimodal multiple prediction progress quality quality data reliability survey type