Titlebook: Computer Vision – ECCV 2022 Workshops; Tel Aviv, Israel, Oc Leonid Karlinsky,Tomer Michaeli,Ko Nishino Conference proceedings 2023 The Edit

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Professional Attitudes toward Parentsotography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first

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Discussion of Results and Conclusions,the light propagation process, the images captured by the UDC system usually contain flare, haze, blur, and noise. Particularly, flare and blur in UDC images could severely deteriorate the user experience in high dynamic range (HDR) scenes. In this paper, we propose a new deep model, namely UDC-UNet

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Theodore P. Williams,B. N. Baker) demonstrate practical applicability in smartphones, laptops, tablets, and other scenarios. However, the images captured by UDCs suffer from complex image degradation issues, such as flare, haze, blur, and noise. To solve the above issues, we present an Enhanced Coarse-to-Fine Network (ECFNet) to e

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Light Damage in Dystrophic and Normal Ratsls, which can improve the image quality by averaging four pixels in the 2.2 neighborhood under low light conditions. From low-resolution Bayer to full-resolution Bayer has become a very challenging research, especially in the presence of noise. Considering denoise and remosaic, we propose a general

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