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Cited by 713

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Deep photo: model-based photograph enhancement and viewing

Open access
Kopf, Johannes, Neubert, Boris, Chen, Billy, Cohen, Michael, Cohen-Or, Daniel, Deussen, Oliver, Uyttendaele, Matt, Lischinski, Dani·2008·ACM Transactions on Graphics

Abstract

In this paper, we introduce a novel system for browsing, enhancing, and manipulating casual outdoor photographs by combining them with already existing georeferenced digital terrain and urban models. A simple interactive registration process is used to align a photograph with such a model. Once the photograph and the model have been registered, an abundance of information, such as depth, texture, and GIS data, becomes immediately available to our system. This information, in turn, enables a variety of operations, ranging from dehazing and relighting the photograph, to novel view synthesis, and overlaying with geographic information. We describe the implementation of a number of these applications and discuss possible extensions. Our results show that augmenting photographs with already available 3D models of the world supports a wide variety of new ways for us to experience and interact with our everyday snapshots.

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Metadata

Authors
Kopf, J., Neubert, B., Chen, B., Cohen, M., Cohen-Or, D., Deussen, O., Uyttendaele, M., & Lischinski, D.
Venue
ACM Transactions on Graphics
Published
2008-12
Volume
27
Issue
5
Pages
1-10
ISSN
  • 0730-0301 (ISSN-L)
  • 1557-7368
OpenAlex
W2081418206
Cited by
713
References
1
FWCI
47.67
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Deep photo: model-based photograph enhancement and viewing. https://app.cochat.ai/papers/10.1145/1409060.1409069
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Kopf, J., Neubert, B., Chen, B., Cohen, M., Cohen-Or, D., Deussen, O., Uyttendaele, M., & Lischinski, D. (2008). Deep photo: model-based photograph enhancement and viewing. ACM Transactions on Graphics. https://doi.org/10.1145/1409060.1409069

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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.