13 papers
DiTCtrl: Exploring Attention Control in Multi-Modal Diffusion Transformer for Tuning-Free Multi-Prompt Longer Video Generation
Minghong Cai, Xiaodong Cun, Xiaoyu Li +5
Sora-like video generation models have achieved remarkable progress with a Multi-Modal Diffusion Transformer MM-DiT architecture. However, the current video generation models predo…
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…
CustomCrafter: Customized Video Generation with Preserving Motion and Concept Composition Abilities
Tao Wu, Yong Zhang, Xintao Wang +5
Customized video generation aims to generate high-quality videos guided by text prompts and subject's reference images. However, since it is only trained on static images, the fine…
CustomTTT: Motion and Appearance Customized Video Generation via Test-Time Training
Xiuli Bi, Jian Lu, Bo Liu +4
Benefiting from large-scale pre-training of text-video pairs, current text-to-video (T2V) diffusion models can generate high-quality videos from the text description. Besides, give…
DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videos
Wenbo Hu, Xiangjun Gao, Xiaoyu Li +5
Estimating video depth in open-world scenarios is challenging due to the diversity of videos in appearance, content motion, camera movement, and length. We present DepthCrafter, an…
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.…