IDAM-RAW: a sensor-aware RAW imaging framework for low-light perception via illumination decoupling and adaptive feature modulation
This paper proposes IDAM-RAW, a unified RAW-domain framework that bridges physical imaging processes and detection-oriented representation learning through task-driven end-to-end optimization, and DetISP maps RAW measurements to detection-friendly features without relying on fixed hardware ISP processing.