F. Pitié

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Graph-cut techniques for depth and disparity estimations are known to be powerful but also slow. We propose a graph-cut framework that is able to estimate depth maps from a set of candidate values. By employing a restricted set of candidates for each pixel, rough depth maps can be effectively refined to be accurate, smooth and continuous. The contribution(More)
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