Regression with residual neural network for vanishing point detection

被引：10

作者：

Choi, Han-Soo ^{[1
]}

An, Keunhoi ^{[1
]}

Kang, Myungjoo ^{[2
]}

机构：

[1] Seoul Natl Univ, Dept Computat Sci & Technol, Seoul, South Korea

[2] Seoul Natl Univ, Dept Math Sci, Seoul, South Korea

来源：

IMAGE AND VISION COMPUTING | 2019年 / 91卷

基金：

新加坡国家研究基金会;

关键词：

Vanishing point detection; Deep learning; Naver Street View dataset; ResNet; Regression;

D O I：

10.1016/j.imavis.2019.08.001

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper aims to propose a regression method with a residual neural network (ResNet) for vanishing point detection. The purpose of this study is to estimate the position of the vanishing point accurately. Our newly collected Naver Maps' Street View dataset is used for training regression ResNet-34 and for comparison with previous methods. It is concluded that the trained regression ResNet outperforms previous methods in terms of both computation time and accuracy. (C) 2019 Elsevier B.V. All rights reserved.

引用

页数：8

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