OmnimatteRF: Robust Omnimatte with 3D Background Modeling

Geng Lin, Chen Gao, Jia-Bin Huang, Changil Kim, Yipeng Wang +2 more
2/14/2026

No official code found. Best implementation: facebookresearch/OmnimatteRF (147 stars, MIT, last commit 2023-09-15).

Abstract

Video matting has broad applications, from adding interesting effects to casually captured movies to assisting video production professionals. Matting with associated effects such as shadows and reflections has also attracted increasing research activity, and methods like Omnimatte have been proposed to separate dynamic foreground objects of interest into their own layers. However, prior works represent video backgrounds as 2D image layers, limiting their capacity to express more complicated scenes, thus hindering application to real-world videos. In this paper, we propose a novel video matting method, OmnimatteRF, that combines dynamic 2D foreground layers and a 3D background model. The 2D layers preserve the details of the subjects, while the 3D background robustly reconstructs scenes in real-world videos. Extensive experiments demonstrate that our method reconstructs scenes with better quality on various videos.

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Code Implementations(1)

MIT

A matting method that combines dynamic 2D foreground layers and a 3D background model.

14715Shell, PythonAug 23, 20233 years agoMIT

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Cite this paper

@article{lin2026omnimatterf,
  title  = {OmnimatteRF: Robust Omnimatte with 3D Background Modeling},
  author = {Geng Lin and Chen Gao and Jia-Bin Huang and Changil Kim and Yipeng Wang and Matthias Zwicker and Ayush Saraf},
  year   = {2026},
  eprint = {2309.07749},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2309.07749},
  journal = {ICCV 2023 2023}
}

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