7 papers
End-to-End Training for Autoregressive Video Diffusion via Self-Resampling
Yuwei Guo, Ceyuan Yang, Hao He +5
Autoregressive video diffusion models hold promise for world simulation but are vulnerable to exposure bias arising from the train-test mismatch. While recent works address this vi…
Multi-identity Human Image Animation with Structural Video Diffusion
Zhenzhi Wang, Yixuan Li, Yanhong Zeng +4
Generating human videos from a single image while ensuring high visual quality and precise control is a challenging task, especially in complex scenarios involving multiple individ…
SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree
Shuangrui Ding, Rui Qian, Xiaoyi Dong +6
The Segment Anything Model 2 (SAM 2) has emerged as a powerful foundation model for object segmentation in both images and videos, paving the way for various downstream video appli…
Long Context Tuning for Video Generation
Yuwei Guo, Ceyuan Yang, Ziyan Yang +5
Recent advances in video generation can produce realistic, minute-long single-shot videos with scalable diffusion transformers. However, real-world narrative videos require multi-s…
CameraCtrl: Enabling Camera Control for Text-to-Video Generation
Hao He, Yinghao Xu, Yuwei Guo +4
Controllability plays a crucial role in video generation, as it allows users to create and edit content more precisely. Existing models, however, lack control of camera pose that s…
Imagine360: Immersive 360 Video Generation from Perspective Anchor
Jing Tan, Shuai Yang, Tong Wu +4
videos offer a hyper-immersive experience that allows the viewers to explore a dynamic scene from full 360 degrees. To achieve more user-friendly and personalized conte…