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  1. Chapter and Conference Paper

    Learning CRFs Using Graph Cuts

    Many computer vision problems are naturally formulated as random fields, specifically MRFs or CRFs. The introduction of graph cuts has enabled efficient and optimal inference in associative random fields, grea...

    Martin Szummer, Pushmeet Kohli, Derek Hoiem in Computer Vision – ECCV 2008 (2008)

  2. Chapter and Conference Paper

    Measuring Uncertainty in Graph Cut Solutions – Efficiently Computing Min-marginal Energies Using Dynamic Graph Cuts

    In recent years the use of graph-cuts has become quite popular in computer vision. However, researchers have repeatedly asked the question whether it might be possible to compute a measure of uncertainty assoc...

    Pushmeet Kohli, Philip H. S. Torr in Computer Vision – ECCV 2006 (2006)

  3. Chapter and Conference Paper

    PoseCut: Simultaneous Segmentation and 3D Pose Estimation of Humans Using Dynamic Graph-Cuts

    We present a novel algorithm for performing integrated segmentation and 3D pose estimation of a human body from multiple views. Unlike other related state of the art techniques which focus on either segmentation ...

    Matthieu Bray, Pushmeet Kohli, Philip H. S. Torr in Computer Vision – ECCV 2006 (2006)

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