Semantic Line Combination Detector

Fuente: arXiv
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Autori principali: Ko, Jinwon, Jin, Dongkwon, Kim, Chang-Su
Natura: Preprint
Pubblicazione: 2024
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author Ko, Jinwon
Jin, Dongkwon
Kim, Chang-Su
author_facet Ko, Jinwon
Jin, Dongkwon
Kim, Chang-Su
contents A novel algorithm, called semantic line combination detector (SLCD), to find an optimal combination of semantic lines is proposed in this paper. It processes all lines in each line combination at once to assess the overall harmony of the lines. First, we generate various line combinations from reliable lines. Second, we estimate the score of each line combination and determine the best one. Experimental results demonstrate that the proposed SLCD outperforms existing semantic line detectors on various datasets. Moreover, it is shown that SLCD can be applied effectively to three vision tasks of vanishing point detection, symmetry axis detection, and composition-based image retrieval. Our codes are available at https://github.com/Jinwon-Ko/SLCD.
format Preprint
id arxiv_https___arxiv_org_abs_2404_18399
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Semantic Line Combination Detector
Ko, Jinwon
Jin, Dongkwon
Kim, Chang-Su
Computer Vision and Pattern Recognition
A novel algorithm, called semantic line combination detector (SLCD), to find an optimal combination of semantic lines is proposed in this paper. It processes all lines in each line combination at once to assess the overall harmony of the lines. First, we generate various line combinations from reliable lines. Second, we estimate the score of each line combination and determine the best one. Experimental results demonstrate that the proposed SLCD outperforms existing semantic line detectors on various datasets. Moreover, it is shown that SLCD can be applied effectively to three vision tasks of vanishing point detection, symmetry axis detection, and composition-based image retrieval. Our codes are available at https://github.com/Jinwon-Ko/SLCD.
title Semantic Line Combination Detector
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2404.18399