36 citations · 38 across the 8 of their papers we have counts for
9 papers
FSVideo: Fast Speed Video Diffusion Model in a Highly-Compressed Latent Space
FSVideo Team, Qingyu Chen, Zhiyuan Fang +17
We introduce FSVideo, a fast speed transformer-based image-to-video (I2V) diffusion framework. We build our framework on the following key components: 1.) a new video autoencoder w…
ATI: Any Trajectory Instruction for Controllable Video Generation
Angtian Wang, Haibin Huang, Jacob Zhiyuan Fang +2
We propose a unified framework for motion control in video generation that seamlessly integrates camera movement, object-level translation, and fine-grained local motion using traj…
MAGREF: Masked Guidance for Any-Reference Video Generation with Subject Disentanglement
Yufan Deng, Yuanyang Yin, Xun Guo +8
We tackle the task of any-reference video generation, which aims to synthesize videos conditioned on arbitrary types and combinations of reference subjects, together with textual p…
CINEMA: Coherent Multi-Subject Video Generation via MLLM-Based Guidance
Yufan Deng, Xun Guo, Yizhi Wang +7
Video generation has witnessed remarkable progress with the advent of deep generative models, particularly diffusion models. While existing methods excel in generating high-quality…
ViMo: Generating Motions from Casual Videos
Liangdong Qiu, Chengxing Yu, Yanran Li +6
Although humans have the innate ability to imagine multiple possible actions from videos, it remains an extraordinary challenge for computers due to the intricate camera movements…
Spatial and Surface Correspondence Field for Interaction Transfer
Zeyu Huang, Honghao Xu, Haibin Huang +3
In this paper, we introduce a new method for the task of interaction transfer. Given an example interaction between a source object and an agent, our method can automatically infer…
Direct-a-Video: Customized Video Generation with User-Directed Camera Movement and Object Motion
Shiyuan Yang, Liang Hou, Haibin Huang +5
Recent text-to-video diffusion models have achieved impressive progress. In practice, users often desire the ability to control object motion and camera movement independently for…
MotionCrafter: One-Shot Motion Customization of Diffusion Models
Yuxin Zhang, Fan Tang, Nisha Huang +4
The essence of a video lies in its dynamic motions, including character actions, object movements, and camera movements. While text-to-video generative diffusion models have recent…
I2V-Adapter: A General Image-to-Video Adapter for Diffusion Models
Xun Guo, Mingwu Zheng, Liang Hou +9
Text-guided image-to-video (I2V) generation aims to generate a coherent video that preserves the identity of the input image and semantically aligns with the input prompt. Existing…