Video Text
Video text research focuses on bridging the semantic gap between visual and textual information in videos, aiming to improve tasks like video retrieval, generation, and understanding. Current efforts concentrate on developing sophisticated multimodal models, often leveraging transformer architectures and diffusion models, to effectively integrate textual descriptions with video content, including advancements in temporal modeling and data augmentation techniques. This field is significant for advancing artificial intelligence capabilities in multimedia analysis and generation, with applications ranging from improved search engines to more realistic video synthesis and editing tools.
Papers
TALC: Time-Aligned Captions for Multi-Scene Text-to-Video Generation
Hritik Bansal, Yonatan Bitton, Michal Yarom, Idan Szpektor, Aditya Grover, Kai-Wei Chang
Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition
Hao Fei, Shengqiong Wu, Wei Ji, Hanwang Zhang, Meishan Zhang, Mong-Li Lee, Wynne Hsu