SDE-AWB: a Generic Solution for 2nd International Illumination Estimation Challenge
We propose a neural network-based solution for three different tracks of 2nd International Illumination Estimation Challenge (chromaticity.iitp.ru). Our method is built on pre-trained Squeeze-Net backbone, differential 2D chroma histogram layer and a shallow MLP utilizing Exif information. By combin...
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creator | Qian, Yanlin Feng, Sibo Qian, Kang Wang, Miaofeng |
description | We propose a neural network-based solution for three different tracks of 2nd
International Illumination Estimation Challenge (chromaticity.iitp.ru). Our
method is built on pre-trained Squeeze-Net backbone, differential 2D chroma
histogram layer and a shallow MLP utilizing Exif information. By combining
semantic feature, color feature and Exif metadata, the resulting method --
SDE-AWB -- obtains 1st place in both indoor and two-illuminant tracks and 2nd
place in general track. |
doi_str_mv | 10.48550/arxiv.2010.05149 |
format | Article |
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International Illumination Estimation Challenge (chromaticity.iitp.ru). Our
method is built on pre-trained Squeeze-Net backbone, differential 2D chroma
histogram layer and a shallow MLP utilizing Exif information. By combining
semantic feature, color feature and Exif metadata, the resulting method --
SDE-AWB -- obtains 1st place in both indoor and two-illuminant tracks and 2nd
place in general track.</description><identifier>DOI: 10.48550/arxiv.2010.05149</identifier><language>eng</language><subject>Computer Science - Computer Vision and Pattern Recognition</subject><creationdate>2020-10</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2010.05149$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2010.05149$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Qian, Yanlin</creatorcontrib><creatorcontrib>Feng, Sibo</creatorcontrib><creatorcontrib>Qian, Kang</creatorcontrib><creatorcontrib>Wang, Miaofeng</creatorcontrib><title>SDE-AWB: a Generic Solution for 2nd International Illumination Estimation Challenge</title><description>We propose a neural network-based solution for three different tracks of 2nd
International Illumination Estimation Challenge (chromaticity.iitp.ru). Our
method is built on pre-trained Squeeze-Net backbone, differential 2D chroma
histogram layer and a shallow MLP utilizing Exif information. By combining
semantic feature, color feature and Exif metadata, the resulting method --
SDE-AWB -- obtains 1st place in both indoor and two-illuminant tracks and 2nd
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International Illumination Estimation Challenge (chromaticity.iitp.ru). Our
method is built on pre-trained Squeeze-Net backbone, differential 2D chroma
histogram layer and a shallow MLP utilizing Exif information. By combining
semantic feature, color feature and Exif metadata, the resulting method --
SDE-AWB -- obtains 1st place in both indoor and two-illuminant tracks and 2nd
place in general track.</abstract><doi>10.48550/arxiv.2010.05149</doi><oa>free_for_read</oa></addata></record> |
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title | SDE-AWB: a Generic Solution for 2nd International Illumination Estimation Challenge |
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