Result details - ETH3D

Submitted by Nikolai Smolyanskiy.

Submission data

Full name	NVStereoNet: An Efficient Semi-Supervised Deep Neural Network Approach
Description	We propose a novel semi-supervised learning approach to training a deep stereo neural network, along with a novel architecture containing a machine-learned argmax layer and a custom, publicly available runtime that enables a smaller version of our stereo DNN to run on an embedded GPU.
Publication title	On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach
Publication authors	Nikolai Smolyanskiy, Alexey Kamenev, Stan Birchfield
Publication venue	Arxiv
Publication URL	https://arxiv.org/abs/1803.09719
Programming language(s)	TensorFlow
Hardware	Titan XP
Submission creation date	1 Jun, 2018
Last edited	1 Jun, 2018

High-res multi-view results

Info	all	high-res multi-view	indoor	outdoor	courty.	delive.	electro	facade	kicker	meadow	office	pipes	playgr.	relief	relief.	terrace	terrai.
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Low-res many-view results

Info	all	low-res many-view	indoor	outdoor	lakeside	sand box	storage room	storage room 2	tunnel
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Low-res two-view results

Info	all	lakes. 1l	lakes. 1s	sand box 1l	sand box 1s	stora. room 1l	stora. room 1s	stora. room 2l	stora. room 2s	stora. room 2 1l	stora. room 2 1s	stora. room 2 2l	stora. room 2 2s	stora. room 3l	stora. room 3s	tunnel 1l	tunnel 1s	tunnel 2l	tunnel 2s	tunnel 3l	tunnel 3s
	0.67	0.49	0.83	0.48	0.40	0.51	0.46	0.70	0.77	0.84	1.72	1.02	0.83	1.23	0.79	0.32	0.38	0.40	0.46	0.36	0.41

SLAM results

		all	boxes	boxes dark	buddha	cables 4	cables 5	desk 1	desk 2	desk changing 2	desk dark 1	desk dark 2	desk global light changes	desk ir light	dino	drone	foreground occlusion	helmet	kidnap 2	lamp	large loop 2	large loop 3	large non loop	motion 2	motion 3	motion 4	planar 1	reflective 2	scale change	table 1	table 2	table 5	table 6	table global light changes	table local light changes	table scene	trashbin
	Method	Info
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