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- W4312791683 abstract "Imaging in low light is extremely challenging due to low photon counts. Using sensitive CMOS cameras, it is currently possible to take videos at night under moonlight (0.05-0.3 lux illumination). In this paper, we demonstrate photorealistic video under starlight (no moon present, <0.001 lux) for the first time. To enable this, we develop a GAN-tuned physics-based noise model to more accurately represent camera noise at the lowest light levels. Using this noise model, we train a video denoiser using a combination of simulated noisy video clips and real noisy still images. We capture a 5–10 fps video dataset with significant motion at approximately 0.6-0.7 millilux with no active illumination. Comparing against alternative methods, we achieve improved video quality at the lowest light levels, demonstrating photorealistic video denoising in starlight for the first time." @default.
- W4312791683 created "2023-01-05" @default.
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- W4312791683 date "2022-06-01" @default.
- W4312791683 modified "2023-10-16" @default.
- W4312791683 title "Dancing under the stars: video denoising in starlight" @default.
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- W4312791683 doi "https://doi.org/10.1109/cvpr52688.2022.01576" @default.
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