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

37 citations · 123 across the 32 of their papers we have counts for

collaborators

32 papers

cs.CV2024

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…

cs.CV2024★ 1 cited

StyleMaster: Stylize Your Video with Artistic Generation and Translation

Zixuan Ye, Huijuan Huang, Xintao Wang +3

Style control has been popular in video generation models. Existing methods often generate videos far from the given style, cause content leakage, and struggle to transfer one vide…

cs.CV2024

NovelGS: Consistent Novel-view Denoising via Large Gaussian Reconstruction Model

Jinpeng Liu, Jiale Xu, Weihao Cheng +4

We introduce NovelGS, a diffusion model for Gaussian Splatting (GS) given sparse-view images. Recent works leverage feed-forward networks to generate pixel-aligned Gaussians, which…

cs.CV2024★ 4 cited

Analysis and Benchmarking of Extending Blind Face Image Restoration to Videos

Zhouxia Wang, Jiawei Zhang, Xintao Wang +4

Recent progress in blind face restoration has resulted in producing high-quality restored results for static images. However, efforts to extend these advancements to video scenario…

cs.CV2024

Story3D-Agent: Exploring 3D Storytelling Visualization with Large Language Models

Yuzhou Huang, Yiran Qin, Shunlin Lu +4

Traditional visual storytelling is complex, requiring specialized knowledge and substantial resources, yet often constrained by human creativity and creation precision. While Large…

cs.CV2024

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…

cs.CV2024★ 2 cited

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…

cs.CV2024

Image Conductor: Precision Control for Interactive Video Synthesis

Yaowei Li, Xintao Wang, Zhaoyang Zhang +5

Filmmaking and animation production often require sophisticated techniques for coordinating camera transitions and object movements, typically involving labor-intensive real-world…

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

ReVideo: Remake a Video with Motion and Content Control

Chong Mou, Mingdeng Cao, Xintao Wang +3

Despite significant advancements in video generation and editing using diffusion models, achieving accurate and localized video editing remains a substantial challenge. Additionall…

cs.CV2024

MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Model

Muyao Niu, Xiaodong Cun, Xintao Wang +3

We present MOFA-Video, an advanced controllable image animation method that generates video from the given image using various additional controllable signals (such as human landma…

cs.CV2024★ 18 cited

InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models

Jiale Xu, Weihao Cheng, Yiming Gao +3

We present InstantMesh, a feed-forward framework for instant 3D mesh generation from a single image, featuring state-of-the-art generation quality and significant training scalabil…

cs.CV2024

SphereDiffusion: Spherical Geometry-Aware Distortion Resilient Diffusion Model

Tao Wu, Xuewei Li, Zhongang Qi +4

Controllable spherical panoramic image generation holds substantial applicative potential across a variety of domains.However, it remains a challenging task due to the inherent sph…

cs.CV2024★ 2 cited

BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion

Xuan Ju, Xian Liu, Xintao Wang +3

Image inpainting, the process of restoring corrupted images, has seen significant advancements with the advent of diffusion models (DMs). Despite these advancements, current DM ada…

cs.CV2024

DiffEditor: Boosting Accuracy and Flexibility on Diffusion-based Image Editing

Chong Mou, Xintao Wang, Jiechong Song +2

Large-scale Text-to-Image (T2I) diffusion models have revolutionized image generation over the last few years. Although owning diverse and high-quality generation capabilities, tra…

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,…

cs.CV2024★ 2 cited

Towards A Better Metric for Text-to-Video Generation

Jay Zhangjie Wu, Guian Fang, Haoning Wu +11

Generative models have demonstrated remarkable capability in synthesizing high-quality text, images, and videos. For video generation, contemporary text-to-video models exhibit imp…

cs.CV2023

SmartEdit: Exploring Complex Instruction-based Image Editing with Multimodal Large Language Models

Yuzhou Huang, Liangbin Xie, Xintao Wang +8

Current instruction-based editing methods, such as InstructPix2Pix, often fail to produce satisfactory results in complex scenarios due to their dependence on the simple CLIP text…

cs.CV2023★ 1 cited

PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding

Zhen Li, Mingdeng Cao, Xintao Wang +3

Recent advances in text-to-image generation have made remarkable progress in synthesizing realistic human photos conditioned on given text prompts. However, existing personalized g…

cs.CV2023★ 1 cited

AnimateZero: Video Diffusion Models are Zero-Shot Image Animators

Jiwen Yu, Xiaodong Cun, Chenyang Qi +4

Large-scale text-to-video (T2V) diffusion models have great progress in recent years in terms of visual quality, motion and temporal consistency. However, the generation process is…

cs.CV2023★ 1 cited

MotionCtrl: A Unified and Flexible Motion Controller for Video Generation

Zhouxia Wang, Ziyang Yuan, Xintao Wang +4

Motions in a video primarily consist of camera motion, induced by camera movement, and object motion, resulting from object movement. Accurate control of both camera and object mot…

cs.CV2023★ 3 cited

MagicStick: Controllable Video Editing via Control Handle Transformations

Yue Ma, Xiaodong Cun, Sen Liang +5

Text-based video editing has recently attracted considerable interest in changing the style or replacing the objects with a similar structure. Beyond this, we demonstrate that prop…

cs.CV2023

StyleCrafter: Enhancing Stylized Text-to-Video Generation with Style Adapter

Gongye Liu, Menghan Xia, Yong Zhang +6

Text-to-video (T2V) models have shown remarkable capabilities in generating diverse videos. However, they struggle to produce user-desired stylized videos due to (i) text's inheren…