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Titlebook: Computer Vision – ACCV 2020; 15th Asian Conferenc Hiroshi Ishikawa,Cheng-Lin Liu,Jianbo Shi Conference proceedings 2021 Springer Nature Swi

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Raw-Guided Enhancing Reprocess of Low-Light Image via Deep Exposure Adjustmentsub-modules for unprocessing, reconstruction and processing, respectively. To the best of our knowledge, the proposed sub-net for unprocessing is the first learning-based unprocessing method. After the joint training of three parts, each pre-trained seperately with the RAW image guidance, experiment
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Robust High Dynamic Range (HDR) Imaging with Complex Motion and Parallaxitly. To make full use of aligned features, we use dilated dense residual blocks with squeeze-and-excitation (SE) attention. Such attention mechanism effectively helps to remove redundant information and suppress misaligned features. Additional mask-based weighting is further employed to refine the
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