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Cited by 458

The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.

A Generalized Low-Rank Appearance Model for Spatio-temporally Correlated Rain Streaks

Chen, Yi-Lei, Hsu, Chiou-Ting·2013·2013 IEEE International Conference on Computer Vision

Abstract

In this paper, we propose a novel low-rank appearance model for removing rain streaks. Different from previous work, our method needs neither rain pixel detection nor time-consuming dictionary learning stage. Instead, as rain streaks usually reveal similar and repeated patterns on imaging scene, we propose and generalize a low-rank model from matrix to tensor structure in order to capture the spatio-temporally correlated rain streaks. With the appearance model, we thus remove rain streaks from image/video (and also other high-order image structure) in a unified way. Our experimental results demonstrate competitive (or even better) visual quality and efficient run-time in comparison with state of the art.

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Metadata

Authors
Chen, Y.-L., & Hsu, C.-T.
Venue
2013 IEEE International Conference on Computer Vision
Publisher
IEEE
Published
2013-12
Pages
1968-1975
OpenAlex
W2154621477
Cited by
458
References
23
FWCI
3.20
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: A Generalized Low-Rank Appearance Model for Spatio-temporally Correlated Rain Streaks. https://app.cochat.ai/papers/10.1109/iccv.2013.247
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Chen, Y.-L., & Hsu, C.-T. (2013). A Generalized Low-Rank Appearance Model for Spatio-temporally Correlated Rain Streaks. 2013 IEEE International Conference on Computer Vision. https://doi.org/10.1109/iccv.2013.247

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