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Feature Ensemble Network with Occlusion Disambiguation for Accurate Patch-Based Stereo Matching
2017
IEICE transactions on information and systems
Accurate stereo matching remains a challenging problem in case of weakly-textured areas, discontinuities and occlusions. In this letter, a novel stereo matching method, consisting of leveraging feature ensemble network to compute matching cost, error detection network to predict outliers and priority-based occlusion disambiguation for refinement, is presented. Experiments on the Middlebury benchmark demonstrate that the proposed method yields competitive results against the state-of-the-art
doi:10.1587/transinf.2017edl8122
fatcat:mqrswykkw5coxdskrjutchb7ae