The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Video Inpainting of Complex Scenes
Open accessAbstract
We propose an automatic video inpainting algorithm which relies on the optimization of a global, patch-based functional. Our algorithm is able to deal with a variety of challenging situations which naturally arise in video inpainting, such as the correct reconstruction of dynamic textures, multiple moving objects, and moving background. Furthermore, we achieve this in an order of magnitude less execution time with respect to the state-of-the-art. We are also able to achieve good quality results on high-definition videos. Finally, we provide specific algorithmic details to make implementation of our algorithm as easy as possible. The resulting algorithm requires no segmentation or manual input other than the definition of the inpainting mask and can deal with a wider variety of situations than is handled by previous work.
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Citations
Cites
Fast approximate energy minimization via graph cuts
Boykov, Y., Veksler, O., & Zabih, R. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.969114 · Cited by 6,988
Metadata
- Authors
- Newson, A., Almansa, A., Fradet, M., Gousseau, Y., & Pérez, P.
- Venue
- SIAM Journal on Imaging Sciences
- Published
- 2014-01
- Volume
- 7
- Issue
- 4
- Pages
- 1993-2019
- ISSN
- 1936-4954 (ISSN-L)
- OpenAlex
- W2069237980
- Cited by
- 261
- References
- 1
- FWCI
- 14.54
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Video Inpainting of Complex Scenes. https://app.cochat.ai/papers/10.1137/140954933
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- Newson, A., Almansa, A., Fradet, M., Gousseau, Y., & Pérez, P. (2014). Video Inpainting of Complex Scenes. SIAM Journal on Imaging Sciences. https://doi.org/10.1137/140954933
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
