Modeling Multimodal Clues in a Hybrid Deep Learning Framework for Video Classification.

Videos are inherently multimodal. This paper studies the problem of exploiting the abundant multimodal clues for improved video classification performance. We introduce a novel hybrid deep learning framework that integrates useful clues from multiple modalities, including static spatial appearance information, motion patterns within a short time window, audio information, as well as long-range tem...