TY  - CONF
AU  - Patricia Suarez
AU  - Dario Carpio
AU  - Angel Sappa
A2  - ISVC
PY  - 2021//
TI  - Non-homogeneous Haze Removal Through a Multiple Attention Module Architecture
T2  - LNCS
BT  - 16th International Symposium on Visual Computing
SP  - 178–190
VL  - 13018
N2  - 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.
UR  - https://link.springer.com/chapter/10.1007/978-3-030-90436-4_14
N1  - MSIAU
ID  - Patricia Suarez2021
ER  -