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).
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引用它的顶会 Paper16
- DiffDecompose: Layer-Wise Decomposition of Alpha-Composited Images via Diffusion TransformersZitong Wang, Hang Zhao, Qianyu Zhou, Xuequan Lu 等CVPR 2026 · 被引用 26 次
- Generative Video Motion Editing with 3D Point TracksYao-Chih Lee, Zhoutong Zhang, Jiahui Huang, Jui-Hsien Wang 等CVPR 2026 · 被引用 23 次
- Precise Object and Effect Removal with Adaptive Target-Aware AttentionJixin Zhao, Zhouxia Wang, Peiqing Yang, Shangchen ZhouCVPR 2026 · 被引用 13 次
- LayerFlow: A Unified Model for Layer-aware Video GenerationSihui Ji, Hao Luo, Xi Chen, Yuanpeng Tu 等SIGGRAPH 2025 · 被引用 12 次
- Object-Centric Latent Action LearningAlbina Klepach, Alexander Nikulin, Ilya Zisman, Denis Tarasov 等AAAI 2026 · 被引用 7 次
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