Papers › Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes

Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes

29 Mar 2022CVPR 2022 1arXiv:2203.15302archive 2025-07-28

Dongkwon Jin, Wonhui Park, Seong-Gyun Jeong, Heeyeon Kwon, Chang-Su Kim

A novel algorithm to detect road lanes in the eigenlane space is proposed in this paper. First, we introduce the notion of eigenlanes, which are data-driven descriptors for structurally diverse lanes, including curved, as well as straight, lanes. To obtain eigenlanes, we perform the best rank-M approximation of a lane matrix containing all lanes in a training set. Second, we generate a set of lane candidates by clustering the training lanes in the eigenlane space. Third, using the lane candidates, we determine an optimal set of lanes by developing an anchor-based detection network, called SIIC-Net. Experimental results demonstrate that the proposed algorithm provides excellent detection performance for structurally diverse lanes. Our codes are available at https://github.com/dongkwonjin/Eigenlanes.

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call_culane_eval_custom dongkwonjin/Eigenlanes/Modeling/culane/code/evaluation/eval_culane_official.py official repository ran Apache-2.0 (permissive) · 5b1117c2c47c0666 · report
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discrete_cross_iou dongkwonjin/Eigenlanes/Modeling/culane/code/evaluation/eval_culane_laneatt.py official repository unverified Apache-2.0 (permissive) · 2c8bbea9efb89e40 · report
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Tasks

ClusteringLane Detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Lane Detection CULane Eigenlanes (ResNet-50) F1 score 77.2 #38 of 63 Archive leaderboard report
Lane Detection CULane Eigenlanes (ResNet-18) F1 score 76.5 #41 of 63 Archive leaderboard report
Lane Detection TuSimple Eigenlanes (ResNet-18) Accuracy 95.62% #31 of 43 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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