Conference 3 Dec - 6 Dec Exhibition 4 Dec - 6 Dec


    Technical Papers

    01 Full Conference1 - Full Conference One Day



    Digital Photography

    Saturday, 06 December

    16:15 - 18:00

    Jasmine Hall

    FlexISP: A Flexible Camera Image Processing Framework

    We replace the traditional imaging pipeline with an end-to-end optimization framework that is aware of the camera model, enforces natural-image priors, and directly solves for a particular output representation (e.g., YUV, DCT), jointly accounting for common image processing steps like demosaicking, denoising, superresolution, achieving superior results.

    Felix Heide, University of British Columbia
    Markus Steinberger, NVIDIA
    Yun-Ta Tsai, NVIDIA
    Nasa Rouf, University of British Columbia
    Dawid Pajak, NVIDIA
    Dikpal Reddy, NVIDIA
    Orazio Gallo, NVIDIA
    Jing Liu, University of California
    Wolfgang Heidrich, University of British Columbia
    Karen Egiazarian, NVIDIA
    Jan Kautz, NVIDIA
    Kari Pulli, NVIDIA

    Fast Burst Images Denoising

    This paper presents a fast denoising method that produces a clean, ghost-free image from a burst of noisy images.

    Ziwei Liu, The Chinese University of Hong Kong
    Lu Yuan, Microsoft Research Asia
    Xiaoou Tang, The Chinese University of Hong Kong
    Matt Uyttendaele, Microsoft Research Technologies
    Jian Sun, Microsoft Research Asia

    Spatial-spectral Encoded Compressive Hyperspectral Imaging

    This paper presents a spatial-spectral encoded compressive hyperspectral (HS) images acquisition scheme (SSCSI) for high-resolution snapshot HS imaging by analyzing and evaluating sparse representations of natural HS images, robust 3D HS images reconstruction from 2D coded projections, and additional applications include 3D HS images compression and denoising.

    Xing Lin, Tsinghua University
    Yebin Liu, Tsinghua University
    Jiamin Wu, Tsinghua University
    Qionghai Dai, Tsinghua University

    Mirror Mirror: Crowdsourcing Better Portraits

    We describe a crowdsourcing method for providing feedback on portrait expressions, and for selecting the most attractive expressions from large video/photo collections.

    Junyan Zhu, University of California
    Aseem Agarwala, Adobe Systems, Inc.
    Alexei Efros, University of California
    Eli Shechtman, Adobe Systems Inc.
    Jue Wang, Adobe Systems Inc.

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