Modular Neural Image Signal Processing
Mahmoud Afifi, Zhongling Wang, Ran Zhang, and Michael S. Brown
Unlike most neural ISPs that treat the entire imaging pipeline as a single black-box network, we decompose the process into standard, interpretable, modular learning-based components. This design requires no manual tuning and enables easier debugging, seamless scaling, cross-camera generalization, and fine-grained customization. It also gives users complete control over every stage of the pipeline and supports unlimited post-editable re-rendering by storing compact raw data within the final image. In addition, it enables learning diverse picture styles with minimal memory overhead and integrates naturally with external image-processing functions.
Paper: https://arxiv.org/abs/2512.08564
Code & Executables: https://github.com/mahmoudnafifi/modu...
https://www.mafifi.info/
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