128 citations · 757 across the 38 of their papers we have counts for
6 papers · 1 filter
Super Encoding Network: Recursive Association of Multi-Modal Encoders for Video Understanding
Boyu Chen, Siran Chen, Kunchang Li +3
Video understanding has been considered as one critical step towards world modeling, which is an important long-term problem in AI research. Recently, multimodal foundation models…
TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos
Fanheng Kong, Jingyuan Zhang, Hongzhi Zhang +7
Videos are unique in their integration of temporal elements, including camera, scene, action, and attribute, along with their dynamic relationships over time. However, existing ben…
Make Your Training Flexible: Towards Deployment-Efficient Video Models
Chenting Wang, Kunchang Li, Tianxiang Jiang +3
Popular video training methods mainly operate on a fixed number of tokens sampled from a predetermined spatiotemporal grid, resulting in sub-optimal accuracy-computation trade-offs…
V-Stylist: Video Stylization via Collaboration and Reflection of MLLM Agents
Zhengrong Yue, Shaobin Zhuang, Kunchang Li +2
Despite the recent advancement in video stylization, most existing methods struggle to render any video with complex transitions, based on an open style description of user query.…
TimeStep Master: Asymmetrical Mixture of Timestep LoRA Experts for Versatile and Efficient Diffusion Models in Vision
Shaobin Zhuang, Yiwei Guo, Yanbo Ding +7
Diffusion models have driven the advancement of vision generation over the past years. However, it is often difficult to apply these large models in downstream tasks, due to massiv…
VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling
Xinhao Li, Yi Wang, Jiashuo Yu +10
Long-context video modeling is critical for multimodal large language models (MLLMs), enabling them to process movies, online video streams, and so on. Despite its advances, handli…