TY  - CONF
AU  - Patricia Suarez
AU  - Angel Sappa
AU  - Boris X. Vintimilla
A2  - CVPRW
PY  - 2017//
TI  - Infrared Image Colorization based on a Triplet DCGAN Architecture
BT  - IEEE Conference on Computer Vision and Pattern Recognition Workshops
N2  - 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 thecolor channels are obtained at the same time.
L1  - http://refbase.cvc.uab.es/files/SSV2017b.pdf
UR  - http://dx.doi.org/10.1109/CVPRW.2017.32
N1  - ADAS; 600.086; 600.118
ID  - Patricia Suarez2017
ER  -