Recursive Video Lane Detection

Dongkwon Jin, Dahyun Kim, Chang-Su Kim; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 8473-8482

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.

Related Material


[pdf] [supp] [arXiv]
[bibtex]
@InProceedings{Jin_2023_ICCV, author = {Jin, Dongkwon and Kim, Dahyun and Kim, Chang-Su}, title = {Recursive Video Lane Detection}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2023}, pages = {8473-8482} }