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1912.04384
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Training Deep Neural Networks to Detect Repeatable 2D Features Using Large Amounts of 3D World Capture Data
9 December 2019
Alexander Mai
Joseph Menke
An Yang
3DV
3DPC
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Papers citing
"Training Deep Neural Networks to Detect Repeatable 2D Features Using Large Amounts of 3D World Capture Data"
5 / 5 papers shown
Title
Matterport3D: Learning from RGB-D Data in Indoor Environments
Angel X. Chang
Angela Dai
Thomas Funkhouser
Maciej Halber
Matthias Nießner
Manolis Savva
Shuran Song
Andy Zeng
Yinda Zhang
3DV
3DPC
208
1,917
0
18 Sep 2017
HPatches: A benchmark and evaluation of handcrafted and learned local descriptors
Vassileios Balntas
Karel Lenc
Andrea Vedaldi
K. Mikolajczyk
106
722
0
19 Apr 2017
ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes
Angela Dai
Angel X. Chang
Manolis Savva
Maciej Halber
Thomas Funkhouser
Matthias Nießner
3DPC
3DV
502
4,084
0
14 Feb 2017
Descriptor Matching with Convolutional Neural Networks: a Comparison to SIFT
Philipp Fischer
Alexey Dosovitskiy
Thomas Brox
87
275
0
22 May 2014
Faster and better: a machine learning approach to corner detection
E. Rosten
R. Porter
Tom Drummond
93
1,920
0
14 Oct 2008
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