Lune

CVPR2025顶会

Generative Omnimatte: Learning to Decompose Video into Layers

Yao-Chih Lee, Erika Lu, Sarah Rumbley, Michal Geyer, Jia-Bin Huang, Tali Dekel, Forrester Cole

2025年份
16顶会引用

摘要

Input video Output: Omnimatte layers Object removal Layer editing See-through foreground Motion retiming Layer resizing + background replacement ActionShot (duplicating + retiming) Figure 1 . Generative Omnimatte. Our method decomposes a video into a set of RGBA omnimatte layers, where each layer consists of a fully-visible object and its associated effects like shadows and reflections. We improve upon existing work by adding a generative video prior, allowing our method to complete occluded regions (top, middle) and handle dynamic backgrounds (bottom).

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 Paper16

问问它们各自怎么用它

它引用的顶会 Paper34

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖