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Author | Patricia Suarez; Dario Carpio; Angel Sappa | ||||
Title | Non-homogeneous Haze Removal Through a Multiple Attention Module Architecture | Type | Conference Article | ||
Year | 2021 | Publication | 16th International Symposium on Visual Computing | Abbreviated Journal | |
Volume | 13018 | Issue | Pages | 178–190 | |
Keywords | |||||
Abstract | This paper presents a novel attention based architecture to remove non-homogeneous haze. The proposed model is focused on obtaining the most representative characteristics of the image, at each learning cycle, by means of adaptive attention modules coupled with a residual learning convolutional network. The latter is based on the Res2Net model. The proposed architecture is trained with just a few set of images. Its performance is evaluated on a public benchmark—images from the non-homogeneous haze NTIRE 2021 challenge—and compared with state of the art approaches reaching the best result. | ||||
Address | Virtual; October 2021 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ISVC | ||
Notes | MSIAU | Approved | no | ||
Call Number | Admin @ si @ SCS2021 | Serial | 3668 | ||
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