activity
20232026
most citedVideoCrafter1: Open Diffusion Models for High-Quality Video Generation

37 citations · 64 across the 23 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024

SynCamMaster: Synchronizing Multi-Camera Video Generation from Diverse Viewpoints

Jianhong Bai, Menghan Xia, Xintao Wang +6

Recent advancements in video diffusion models have shown exceptional abilities in simulating real-world dynamics and maintaining 3D consistency. This progress inspires us to invest…

cs.CV2024

3DTrajMaster: Mastering 3D Trajectory for Multi-Entity Motion in Video Generation

Xiao Fu, Xian Liu, Xintao Wang +7

This paper aims to manipulate multi-entity 3D motions in video generation. Previous methods on controllable video generation primarily leverage 2D control signals to manipulate obj…

cs.CV2024

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…

cs.CV2024

FreeTraj: Tuning-Free Trajectory Control in Video Diffusion Models

Haonan Qiu, Zhaoxi Chen, Zhouxia Wang +3

Diffusion model has demonstrated remarkable capability in video generation, which further sparks interest in introducing trajectory control into the generation process. While exist…

cs.CV2024

ToonCrafter: Generative Cartoon Interpolation

Jinbo Xing, Hanyuan Liu, Menghan Xia +4

We introduce ToonCrafter, a novel approach that transcends traditional correspondence-based cartoon video interpolation, paving the way for generative interpolation. Traditional me…

cs.CV2024★ 1 cited

Make a Cheap Scaling: A Self-Cascade Diffusion Model for Higher-Resolution Adaptation

Lanqing Guo, Yingqing He, Haoxin Chen +9

Diffusion models have proven to be highly effective in image and video generation; however, they encounter challenges in the correct composition of objects when generating images o…

cs.CV2024★ 1 cited

VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models

Haoxin Chen, Yong Zhang, Xiaodong Cun +4

Text-to-video generation aims to produce a video based on a given prompt. Recently, several commercial video models have been able to generate plausible videos with minimal noise,…