37 citations · 85 across the 19 of their papers we have counts for
19 papers · 1 filter
VideoMaker: Zero-shot Customized Video Generation with the Inherent Force of Video Diffusion Models
Tao Wu, Yong Zhang, Xiaodong Cun +6
Zero-shot customized video generation has gained significant attention due to its substantial application potential. Existing methods rely on additional models to extract and injec…
Consistent Human Image and Video Generation with Spatially Conditioned Diffusion
Mingdeng Cao, Chong Mou, Ziyang Yuan +4
Consistent human-centric image and video synthesis aims to generate images or videos with new poses while preserving appearance consistency with a given reference image, which is c…
Noise Calibration: Plug-and-play Content-Preserving Video Enhancement using Pre-trained Video Diffusion Models
Qinyu Yang, Haoxin Chen, Yong Zhang +4
In order to improve the quality of synthesized videos, currently, one predominant method involves retraining an expert diffusion model and then implementing a noising-denoising pro…
MiraData: A Large-Scale Video Dataset with Long Durations and Structured Captions
Xuan Ju, Yiming Gao, Zhaoyang Zhang +6
Sora's high-motion intensity and long consistent videos have significantly impacted the field of video generation, attracting unprecedented attention. However, existing publicly av…
ZeroSmooth: Training-free Diffuser Adaptation for High Frame Rate Video Generation
Shaoshu Yang, Yong Zhang, Xiaodong Cun +2
Video generation has made remarkable progress in recent years, especially since the advent of the video diffusion models. Many video generation models can produce plausible synthet…
CV-VAE: A Compatible Video VAE for Latent Generative Video Models
Sijie Zhao, Yong Zhang, Xiaodong Cun +5
Spatio-temporal compression of videos, utilizing networks such as Variational Autoencoders (VAE), plays a crucial role in OpenAI's SORA and numerous other video generative models.…