| Home | << 1 >> |
|
| Record | |||||
|---|---|---|---|---|---|
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 | |||
| Keywords | |||||
| 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. |
||||
| Address | Honolulu; Hawaii; USA; July 2017 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | CVPRW | ||
| Notes | ADAS; 600.086; 600.118 | Approved | no | ||
| Call Number | Admin @ si @ SSV2017b | Serial | 2920 | ||
| Permanent link to this record | |||||