Learning to Enhance Low-Light Images with a Synthetic-Real Interaction Training Strategy

Recently, utilizing deep networks to improve the visual quality of low-light images has attracted widespread attention. These works attach importance to design the network architecture and loss functions. However, they heavily overlook the strong portrayal ability of the network and a critical factor that decides the performance of deep networks, i.e., training strategy. In this work, we design a ...