Abstract
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. More-over, 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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024 |
| Publisher | IEEE Computer Society |
| Pages | 28066-28075 |
| Number of pages | 10 |
| ISBN (Electronic) | 9798350353006 |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024 - Seattle, United States Duration: 2024 Jun 16 → 2024 Jun 22 |
Publication series
| Name | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
|---|---|
| ISSN (Print) | 1063-6919 |
Conference
| Conference | 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024 |
|---|---|
| Country/Territory | United States |
| City | Seattle |
| Period | 24/6/16 → 24/6/22 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
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