Robust stereo matching with surface normal prediction

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IRS: A Large Synthetic Indoor Robotics Stereo Dataset for Disparity and Surface Normal Estimation (2019, methodology): “Compared to monocular disparity estimation and normal estimation which rely on the prior information of the scene and lack geometric constraints, stereo vision can combine the prior information and geometry information together to give better estimated results [7], [8], [9].”
Semi-global Stereo Matching with Surface Orientation Priors (2017, methodology): “Several recent stereo algorithms [21, 22, 50] use surface normal priors derived from single images [15, 31, 16, 2] These methods utilize continuous optimization and require minimization techniques such as primal-dual methods or linear programming.”