Lune

CVPR2025顶会

ByTheWay: Boost Your Text-to-Video Generation Model to Higher Quality in a Training-free Way

Jiazi Bu, Pengyang Ling, Pan Zhang, Tong Wu, Xiaoyi Dong, Yuhang Zang, Yuhang Cao, Dahua Lin, Jiaqi Wang

2025年份
3顶会引用

摘要

CPII under InnoHK, A dog, playing on the grass, soft lightening, high quality, ... A panda plays in the snow covered forest, 4k resolution, film grain, ... Vanilla ByTheWay Vanilla ByTheWay Enhancing structural plausibility and temporal consistency Enriching motion patterns and amplifying the motion magnitude Figure 1. Unlock the potential of pretrained text-to-video (T2V) generation models in a training-free approach. (1) ByTheWay helps to enhance structural plausibility and temporal consistency in generated videos, significantly reducing artifacts and flickering. (2) ByTheWay contributes to enriching motion patterns and amplifying the motion magnitude in generated videos. Further, ByTheWay can be seamlessly integrated into various powerful T2V backbones (e.g., AnimateDiff[12] and VideoCrafter2[6]) in a plug-and-play manner, serving as a highly extensible module without introducing additional parameters or sampling cost.

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper3

问问它们各自怎么用它

它引用的顶会 Paper24

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖