5 citations · 11 across the 12 of their papers we have counts for
4 papers · 1 filter
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…
VolumeDiffusion: Flexible Text-to-3D Generation with Efficient Volumetric Encoder
Zhicong Tang, Shuyang Gu, Chunyu Wang +4
This paper introduces a pioneering 3D volumetric encoder designed for text-to-3D generation. To scale up the training data for the diffusion model, a lightweight network is develop…
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…
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…