Abstract
A novel algorithm to detect road lanes in videos, called recursive video lane detector (RVLD), is proposed in this paper, which propagates the state of a current frame recursively to the next frame. RVLD consists of an intra-frame lane detector (ILD) and a predictive lane detector (PLD). First, we design ILD to localize lanes in a still frame. Second, we develop PLD to exploit the information of the previous frame for lane detection in a current frame. To this end, we estimate a motion field and warp the previous output to the current frame. Using the warped information, we refine the feature map of the current frame to detect lanes more reliably. Experimental results show that RVLD outperforms existing detectors on video lane datasets. Our codes are available at https://github.com/dongkwonjin/RVLD.
Original language | English |
---|---|
Title of host publication | Proceedings - 2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 8439-8448 |
Number of pages | 10 |
ISBN (Electronic) | 9798350307184 |
DOIs | |
Publication status | Published - 2023 |
Event | 2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023 - Paris, France Duration: 2023 Oct 2 → 2023 Oct 6 |
Publication series
Name | Proceedings of the IEEE International Conference on Computer Vision |
---|---|
ISSN (Print) | 1550-5499 |
Conference
Conference | 2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023 |
---|---|
Country/Territory | France |
City | Paris |
Period | 23/10/2 → 23/10/6 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition