Composite Refinement Network for Unified Image Restoration and Enhancement

CRNet can effectively perform unified image restoration and enhancement tasks by fully integrating information-rich multiple exposure inputs, explicitly separating and strengthening high and low-frequency information, and employing large kernel convolutions and an inverted bottleneck ConvFFN to increase the receptive field and enhance feature fusion.