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Model-blind Video Denoising Via Frame-to-frame Training
[article]
2020
arXiv
pre-print
Modeling the processing chain that has produced a video is a difficult reverse engineering task, even when the camera is available. This makes model based video processing a still more complex task. In this paper we propose a fully blind video denoising method, with two versions off-line and on-line. This is achieved by fine-tuning a pre-trained AWGN denoising network to the video with a novel frame-to-frame training strategy. Our denoiser can be used without knowledge of the origin of the
arXiv:1811.12766v3
fatcat:i3y3zgh7ezggph3u7yzlpqwcpa