Search Results for author:
Found 2 papers, 0 papers with code
BEV-LaneDet: An Efficient 3D Lane Detection Based on Virtual Camera via Key-Points
Experimental results demonstrate that our work outperforms the state-of-the-art approaches in terms of F-Score, being 10. 6% higher on the OpenLane dataset and 4. 0% higher on the Apollo 3D synthetic dataset, with a speed of 185 FPS.
BEV-LaneDet: a Simple and Effective 3D Lane Detection Baseline
Experimental results demonstrate that our work outperforms the state-of-the-art approaches in terms of F-Score, being 10. 6% higher on the OpenLane dataset and 5. 9% higher on the Apollo 3D synthetic dataset, with a speed of 185 FPS.
Ranked #1 on
3D Lane Detection
on Apollo Synthetic 3D Lane
Cannot find the paper you are looking for? You can
Submit a new open access paper.
