Flexible 3D Lane Detection by Hierarchical Shape MatchingFlexible 3D Lane Detection by Hierarchical Shape Matching
<|reference_start|>Flexible 3D Lane Detection by Hierarchical Shape MatchingFlexible 3D Lane Detection by Hierarchical Shape Matching: As one of the basic while vital technologies for HD map construction, 3D lane detection is still an open problem due to varying visual conditions, complex typologies, and strict demands for precision. In this paper, an end-to-end flexible and hierarchical lane detector is proposed to precisely predict 3D lane lines from point clouds. Specifically, we design a hierarchical network predicting flexible representations of lane shapes at different levels, simultaneously collecting global instance semantics and avoiding local errors. In the global scope, we propose to regress parametric curves w.r.t adaptive axes that help to make more robust predictions towards complex scenes, while in the local vision the structure of lane segment is detected in each of the dynamic anchor cells sampled along the global predicted curves. Moreover, corresponding global and local shape matching losses and anchor cell generation strategies are designed. Experiments on two datasets show that we overwhelm current top methods under high precision standards, and full ablation studies also verify each part of our method. Our codes will be released at https://github.com/Doo-do/FHLD.<|reference_end|>
@article{guan2024flexible,
    title={Flexible 3D Lane Detection by Hierarchical Shape MatchingFlexible 3D
  Lane Detection by Hierarchical Shape Matching},
    author={Zhihao Guan, Ruixin Liu, Zejian Yuan, Ao Liu, Kun Tang, Tong Zhou,
  Erlong Li, Chao Zheng, Shuqi Mei},
    journal={arXiv preprint arXiv:2408.07163},
    year={2024},
    doi={10.1609/aaai.v37i1.25146},
    archivePrefix={arXiv},
    eprint={2408.07163},
    primaryClass={cs.CV}
}