Method

SC-SfMLearner (k) [SC-SfMLearner (k)]
https://github.com/JiawangBian/SC-SfMLearner-Release

Submitted on 10 Mar. 2020 07:15 by
Chen Gao (Virginia Tech)

Running time:0.01 s
Environment:1 core @ 2.5 Ghz (C/C++)

Method Description:
SC-SfMLearner (k)(NeurIPS2019), using ORB-SLAM2
Stereo to align scale
Parameters:
0.2
Latex Bibtex:
@inproceedings{bian2019unsupervised,
title={Unsupervised scale-consistent depth and
ego-motion learning from monocular video},
author={Bian, Jiawang and Li, Zhichao and Wang,
Naiyan and Zhan, Huangying and Shen, Chunhua and
Cheng, Ming-Ming and Reid, Ian},
booktitle={NeurIPS},
year={2019}
}

Detailed Results

From all test sequences (sequences 11-21), our benchmark computes translational and rotational errors for all possible subsequences of length (5,10,50,100,150,...,400) meters. Our evaluation ranks methods according to the average of those values, where errors are measured in percent (for translation) and in degrees per meter (for rotation). Details for different trajectory lengths and driving speeds can be found in the plots underneath. Furthermore, the first 5 test trajectories and error plots are shown below.

Test Set Average


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Sequence 11


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Sequence 12


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Sequence 13


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Sequence 14


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Sequence 15


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