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Single View Stereo Matching
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Previous monocular depth estimation methods take a single view and directly regress the expected results. Though recent advances are made by applying geometrically inspired loss functions during training, the inference procedure does not explicitly impose any geometrical constraint. Therefore these models purely rely on the quality of data and the effectiveness of learning to generalize. This either leads to suboptimal results or the demand of huge amount of expensive ground truth labelled data
doi:10.1109/cvpr.2018.00024
dblp:conf/cvpr/LuoRLPSLL18
fatcat:5cm6g3ouljgl7cpmx2k6uwic5y