9 citations · 10 across the 9 of their papers we have counts for
5 papers · 1 filter
DreamVideo: High-Fidelity Image-to-Video Generation with Image Retention and Text Guidance
Cong Wang, Jiaxi Gu, Panwen Hu +3
Image-to-video generation, which aims to generate a video starting from a given reference image, has drawn great attention. Existing methods try to extend pre-trained text-guided i…
BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion Models
Fengyuan Shi, Jiaxi Gu, Hang Xu +3
Diffusion models have made tremendous progress in text-driven image and video generation. Now text-to-image foundation models are widely applied to various downstream image synthes…
MagDiff: Multi-Alignment Diffusion for High-Fidelity Video Generation and Editing
Haoyu Zhao, Tianyi Lu, Jiaxi Gu +5
The diffusion model is widely leveraged for either video generation or video editing. As each field has its task-specific problems, it is difficult to merely develop a single diffu…
Fuse Your Latents: Video Editing with Multi-source Latent Diffusion Models
Tianyi Lu, Xing Zhang, Jiaxi Gu +5
Latent Diffusion Models (LDMs) are renowned for their powerful capabilities in image and video synthesis. Yet, compared to text-to-image (T2I) editing, text-to-video (T2V) editing…
Reuse and Diffuse: Iterative Denoising for Text-to-Video Generation
Jiaxi Gu, Shicong Wang, Haoyu Zhao +7
Inspired by the remarkable success of Latent Diffusion Models (LDMs) for image synthesis, we study LDM for text-to-video generation, which is a formidable challenge due to the comp…