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20212026
most citedVideoCrafter1: Open Diffusion Models for High-Quality Video Generation

37 citations · 143 across the 41 of their papers we have counts for

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Showing 2023Show all

11 papers · 1 filter

cs.CV2023

Segment Anything Model Meets Image Harmonization

Haoxing Chen, Yaohui Li, Zhangxuan Gu +3

Image harmonization is a crucial technique in image composition that aims to seamlessly match the background by adjusting the foreground of composite images. Current methods adopt…

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…

cs.CV2023★ 6 cited

DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors

Jinbo Xing, Menghan Xia, Yong Zhang +6

Animating a still image offers an engaging visual experience. Traditional image animation techniques mainly focus on animating natural scenes with stochastic dynamics (e.g. clouds…

cs.CV2023

Boosting Audio-visual Zero-shot Learning with Large Language Models

Haoxing Chen, Yaohui Li, Yan Hong +6

Audio-visual zero-shot learning aims to recognize unseen classes based on paired audio-visual sequences. Recent methods mainly focus on learning multi-modal features aligned with c…

cs.CV2023★ 37 cited

VideoCrafter1: Open Diffusion Models for High-Quality Video Generation

Haoxin Chen, Menghan Xia, Yingqing He +9

Video generation has increasingly gained interest in both academia and industry. Although commercial tools can generate plausible videos, there is a limited number of open-source m…

cs.CV2023★ 14 cited

ScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Models

Yingqing He, Shaoshu Yang, Haoxin Chen +7

In this work, we investigate the capability of generating images from pre-trained diffusion models at much higher resolutions than the training image sizes. In addition, the genera…

cs.CV2023★ 5 cited

EvalCrafter: Benchmarking and Evaluating Large Video Generation Models

Yaofang Liu, Xiaodong Cun, Xuebo Liu +7

The vision and language generative models have been overgrown in recent years. For video generation, various open-sourced models and public-available services have been developed t…

cs.CV2023★ 5 cited

Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation

Yingqing He, Menghan Xia, Haoxin Chen +8

Generating videos for visual storytelling can be a tedious and complex process that typically requires either live-action filming or graphics animation rendering. To bypass these c…

cs.CV2023★ 2 cited

Make-Your-Video: Customized Video Generation Using Textual and Structural Guidance

Jinbo Xing, Menghan Xia, Yuxin Liu +9

Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential t…

cs.CV2023★ 1 cited

TaleCrafter: Interactive Story Visualization with Multiple Characters

Yuan Gong, Youxin Pang, Xiaodong Cun +8

Accurate Story visualization requires several necessary elements, such as identity consistency across frames, the alignment between plain text and visual content, and a reasonable…

cs.CV2023★ 10 cited

BSNet: Lane Detection via Draw B-spline Curves Nearby

Haoxin Chen, Mengmeng Wang, Yong Liu

Curve-based methods are one of the classic lane detection methods. They learn the holistic representation of lane lines, which is intuitive and concise. However, their performance…