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Image signal processing (ISP) is crucial for camera imaging, and neuralnetworks (NN) solutions are extensively deployed for daytime scenes. The lackof sufficient nighttime image dataset and insights on nighttime illuminationcharacteristics poses a great challenge for high-quality rendering usingexisting NN ISPs. To tackle it, we first built a high-resolution nighttimeRAW-RGB (NR2R) dataset with white balance and tone mapping annotated by expertprofessionals. Meanwhile, to best capture the characteristics of nighttimeillumination light sources, we develop the CBUnet, a two-stage NN ISP tocascade the compensation of color and brightness attributes. Experiments showthat our method has better visual quality compared to traditional ISP pipeline,and is ranked at the second place in the NTIRE 2022 Night Photography RenderingChallenge for two tracks by respective People's and Professional Photographer'schoices. The code and relevant materials are avaiable on our website:https://njuvision.github.io/CBUnet.

Rendering Nighttime Image Via Cascaded Color and Brightness Compensation