TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK	REMOVE
Point Cloud Registration	3DMatch Benchmark	3DMatch + RANSAC	Recall	66.8	# 9
3D Reconstruction	Scan2CAD	3DMatch	Average Accuracy	10.29%	# 2

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3DMatch: Learning Local Geometric Descriptors from RGB-D Reconstructions

CVPR 2017 • Andy Zeng • Shuran Song • Matthias Nießner • Matthew Fisher • Jianxiong Xiao • Thomas Funkhouser

Matching local geometric features on real-world depth images is a challenging task due to the noisy, low-resolution, and incomplete nature of 3D scan data. These difficulties limit the performance of current state-of-art methods, which are typically based on histograms over geometric properties... (read more)