UMLE: Unsupervised Multi-discriminator Network for Low Light Enhancement
Yangyang Qu,Kai Chen,Chao Liu,Yongsheng Ou,Yangyang Qu,Kai Chen,Chao Liu,Yongsheng Ou
Low-light image enhancement is a complex and vital task including, recovering color and texture details from low-light images. For automated driving, low-light scenarios will have severe implications for vision-based applications. To address this problem, we propose a real-time unsupervised generative adversarial network (GAN) with multiple discriminators. It includes a multi-scale discriminator, ...
