1 citations · 2 across the 3 of their papers we have counts for
5 papers · 1 filter
Panacea+: Panoramic and Controllable Video Generation for Autonomous Driving
Yuqing Wen, Yucheng Zhao, Yingfei Liu +7
The field of autonomous driving increasingly demands high-quality annotated video training data. In this paper, we propose Panacea+, a powerful and universally applicable framework…
MicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation
Yanhui Wang, Jianmin Bao, Wenming Weng +12
We present MicroCinema, a straightforward yet effective framework for high-quality and coherent text-to-video generation. Unlike existing approaches that align text prompts with vi…
ARTV: Auto-Regressive Text-to-Video Generation with Diffusion Models
Wenming Weng, Ruoyu Feng, Yanhui Wang +10
We present ARTV, an efficient framework for auto-regressive video generation with diffusion models. Unlike existing methods that generate entire videos in one-s…
Panacea: Panoramic and Controllable Video Generation for Autonomous Driving
Yuqing Wen, Yucheng Zhao, Yingfei Liu +7
The field of autonomous driving increasingly demands high-quality annotated training data. In this paper, we propose Panacea, an innovative approach to generate panoramic and contr…
CCEdit: Creative and Controllable Video Editing via Diffusion Models
Ruoyu Feng, Wenming Weng, Yanhui Wang +5
In this paper, we present CCEdit, a versatile generative video editing framework based on diffusion models. Our approach employs a novel trident network structure that separates st…