TY - GEN
T1 - Line art colorization with concatenated spatial attention
AU - Yuan, Mingcheng
AU - Simo-Serra, Edgar
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - Line art plays a fundamental role in illustration and design, and allows for iteratively polishing designs. However, as they lack color, they can have issues in conveying final designs. In this work, we propose an interactive colorization approach based on a conditional generative adversarial network that takes both the line art and color hints as inputs to produce a high-quality colorized image. Our approach is based on a U-net architecture with a multi-discriminator framework. We propose a Concatenation and Spatial Attention module that is able to generate more consistent and higher quality of line art colorization from user given hints. We evaluate on a large-scale illustration dataset and comparison with existing approaches corroborate the effectiveness of our approach.
AB - Line art plays a fundamental role in illustration and design, and allows for iteratively polishing designs. However, as they lack color, they can have issues in conveying final designs. In this work, we propose an interactive colorization approach based on a conditional generative adversarial network that takes both the line art and color hints as inputs to produce a high-quality colorized image. Our approach is based on a U-net architecture with a multi-discriminator framework. We propose a Concatenation and Spatial Attention module that is able to generate more consistent and higher quality of line art colorization from user given hints. We evaluate on a large-scale illustration dataset and comparison with existing approaches corroborate the effectiveness of our approach.
UR - http://www.scopus.com/inward/record.url?scp=85116002005&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85116002005&partnerID=8YFLogxK
U2 - 10.1109/CVPRW53098.2021.00442
DO - 10.1109/CVPRW53098.2021.00442
M3 - Conference contribution
AN - SCOPUS:85116002005
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 3941
EP - 3945
BT - Proceedings - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
PB - IEEE Computer Society
T2 - 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021
Y2 - 19 June 2021 through 25 June 2021
ER -