Middlebury 2014

Introduced by Daniel Scharstein et al. in High-Resolution Stereo Datasets with Subpixel-Accurate Ground Truth

The Middlebury 2014 dataset contains a set of 23 high resolution stereo pairs for which known camera calibration parameters and ground truth disparity maps obtained with a structured light scanner are available. The images in the Middlebury dataset all show static indoor scenes with varying difficulties including repetitive structures, occlusions, wiry objects as well as untextured areas.

Source: Using Self-Contradiction to Learn Confidence Measures in Stereo Vision


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