{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/clrnet-cross-layer-refinement-network-for","title":"CLRNet: Cross Layer Refinement Network for Lane Detection","arxiv_id":"2203.10350","date":"2022-03-19","proceeding":"CVPR 2022 1","authors":["Tu Zheng","Yifei HUANG","Yang Liu","Wenjian Tang","Zheng Yang","Deng Cai","Xiaofei He"],"abstract":"Lane is critical in the vision navigation system of the intelligent vehicle. Naturally, lane is a traffic sign with high-level semantics, whereas it owns the specific local pattern which needs detailed low-level features to localize accurately. Using different feature levels is of great importance for accurate lane detection, but it is still under-explored. In this work, we present Cross Layer Refinement Network (CLRNet) aiming at fully utilizing both high-level and low-level features in lane detection. In particular, it first detects lanes with high-level semantic features then performs refinement based on low-level features. In this way, we can exploit more contextual information to detect lanes while leveraging local detailed lane features to improve localization accuracy. We present ROIGather to gather global context, which further enhances the feature representation of lanes. In addition to our novel network design, we introduce Line IoU loss which regresses the lane line as a whole unit to improve the localization accuracy. Experiments demonstrate that the proposed method greatly outperforms the state-of-the-art lane detection approaches.","url_abs":"https://arxiv.org/abs/2203.10350v1","url_pdf":"https://arxiv.org/pdf/2203.10350v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"clrnet-cross-layer-refinement-network-for","repo_url":"https://github.com/Turoad/clrnet","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"clrnet-cross-layer-refinement-network-for","repo_url":"https://github.com/Turoad/lanedet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null},{"paper_slug":"clrnet-cross-layer-refinement-network-for","repo_url":"https://github.com/zkyntu/UnLanedet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null},{"paper_slug":"clrnet-cross-layer-refinement-network-for","repo_url":"https://github.com/zkyseu/PPlanedet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"paddle","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"lane-detection","task_name":"Lane Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/lane-detection-on-culane","task":"Lane Detection","dataset":"CULane","model":"CLRNet(DLA-34)","rank_in_archive_order":9,"of":63,"metrics":{"F1 score":"80.47"},"uses_additional_data":false},{"leaderboard":"/sota/lane-detection-on-culane","task":"Lane Detection","dataset":"CULane","model":"CLRNet(ResNet-101)","rank_in_archive_order":14,"of":63,"metrics":{"F1 score":"80.13"},"uses_additional_data":false},{"leaderboard":"/sota/lane-detection-on-culane","task":"Lane Detection","dataset":"CULane","model":"CLRNet(ResNet-34)","rank_in_archive_order":18,"of":63,"metrics":{"F1 score":"79.73"},"uses_additional_data":false},{"leaderboard":"/sota/lane-detection-on-culane","task":"Lane Detection","dataset":"CULane","model":"CLRNet(ResNet-18)","rank_in_archive_order":22,"of":63,"metrics":{"F1 score":"79.58"},"uses_additional_data":false},{"leaderboard":"/sota/lane-detection-on-llamas","task":"Lane Detection","dataset":"LLAMAS","model":"CLRNet (DLA-34)","rank_in_archive_order":1,"of":10,"metrics":{"F1":"0.9612"},"uses_additional_data":false},{"leaderboard":"/sota/lane-detection-on-llamas","task":"Lane Detection","dataset":"LLAMAS","model":"CLRNet (ResNet-18)","rank_in_archive_order":4,"of":10,"metrics":{"F1":"0.9600"},"uses_additional_data":false},{"leaderboard":"/sota/lane-detection-on-tusimple","task":"Lane Detection","dataset":"TuSimple","model":"CLRNet(ResNet-34)","rank_in_archive_order":5,"of":43,"metrics":{"Accuracy":"96.9%","F1 score":"97.82"},"uses_additional_data":false},{"leaderboard":"/sota/lane-detection-on-tusimple","task":"Lane Detection","dataset":"TuSimple","model":"CLRNet(ResNet-18)","rank_in_archive_order":7,"of":43,"metrics":{"Accuracy":"96.82%","F1 score":"97.89"},"uses_additional_data":false},{"leaderboard":"/sota/lane-detection-on-tusimple","task":"Lane Detection","dataset":"TuSimple","model":"CLRNet(ResNet-101)","rank_in_archive_order":41,"of":43,"metrics":{"F1 score":"97.62"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2203.10350","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.10350"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/Turoad/lanedet","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/zkyseu/PPlanedet","reach":{"status":"ok","spdx":"MIT"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/zkyntu/UnLanedet","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/Turoad/clrnet","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"deterministic:regex_extraction","url":"https://github.com/Turoad/CLRNet","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"unverified":4},"by_repo_kind":{"official":{"samples":4,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"473d9d583627843c","entry":"add_args","repo":"Turoad/CLRNet","repo_kind":"official","path":"clrnet/utils/config.py","file_url":"https://github.com/Turoad/CLRNet/blob/HEAD/clrnet/utils/config.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"473d9d583627843c"}},{"code_sha256_prefix":"0fa4d6f8d2df4131","entry":"build_optimizer","repo":"Turoad/CLRNet","repo_kind":"official","path":"clrnet/engine/optimizer.py","file_url":"https://github.com/Turoad/CLRNet/blob/HEAD/clrnet/engine/optimizer.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"0fa4d6f8d2df4131"}},{"code_sha256_prefix":"ee30b884663f26dc","entry":"build_scheduler","repo":"Turoad/CLRNet","repo_kind":"official","path":"clrnet/engine/scheduler.py","file_url":"https://github.com/Turoad/CLRNet/blob/HEAD/clrnet/engine/scheduler.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"ee30b884663f26dc"}},{"code_sha256_prefix":"eb1b7f2b679b1ebf","entry":"nms","repo":"Turoad/CLRNet","repo_kind":"official","path":"clrnet/ops/nms.py","file_url":"https://github.com/Turoad/CLRNet/blob/HEAD/clrnet/ops/nms.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"eb1b7f2b679b1ebf"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}