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Author | Patricia Suarez; Angel Sappa; Boris X. Vintimilla | ||||
Title | Infrared Image Colorization based on a Triplet DCGAN Architecture | Type | Conference Article | ||
Year | 2017 | Publication | IEEE Conference on Computer Vision and Pattern Recognition Workshops | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | This paper proposes a novel approach for colorizing near infrared (NIR) images using Deep Convolutional Generative Adversarial Network (GAN) architectures. The proposed approach is based on the usage of a triplet model for learning each color channel independently, in a more homogeneous way. It allows a fast convergence during the training, obtaining a greater similarity between the given NIR image and the corresponding ground truth. The proposed approach has been evaluated with a large data set of NIR images and compared with a recent approach, which is also based on a GAN architecture but in this case all the
color channels are obtained at the same time. |
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Address | Honolulu; Hawaii; USA; July 2017 | ||||
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Language | Summary Language | Original Title | |||
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Area | Expedition | Conference | CVPRW | ||
Notes | ADAS; 600.086; 600.118 | Approved | no | ||
Call Number | Admin @ si @ SSV2017b | Serial | 2920 | ||
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