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The document presents new algorithms for computing visual correspondence in images using graph cuts, specifically addressing the challenge of occlusions. Existing methods inadequately handle occlusions by treating input images asymmetrically and failing to ensure that each pixel corresponds to at most one pixel in another image. The authors propose two novel methods that maintain the advantages of graph cut algorithms while properly managing occlusions through energy minimization techniques. Experimental results demonstrate the effectiveness of these methods in detecting occlusions and calculating disparities in both stereo and motion contexts.

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