The paper introduces SIED, a calibrated synthetic dataset for extremely low-light RAW enhancement down to 0.0001 lux, and a diffusion-based method with adaptive illumination correction that achieves state-of-the-art restoration.
Low-light image enhancement via breaking down the darkness
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Learning to See in the Extremely Dark
The paper introduces SIED, a calibrated synthetic dataset for extremely low-light RAW enhancement down to 0.0001 lux, and a diffusion-based method with adaptive illumination correction that achieves state-of-the-art restoration.