DRIFT uses a multi-frame network trained with adversarial perceptual loss for alignment, denoising, demosaicing and super-resolution, followed by an efficient deep tone-mapping module that supports tunability and reference consistency.
Lookup table meets lo- cal laplacian filter: pyramid reconstruction network for tone mapping.Advances in Neural Information Processing Sys- tems, 36:57558–57569
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DRIFT: Deep Restoration, ISP Fusion, and Tone-mapping
DRIFT uses a multi-frame network trained with adversarial perceptual loss for alignment, denoising, demosaicing and super-resolution, followed by an efficient deep tone-mapping module that supports tunability and reference consistency.