{"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/online-vectorized-hd-map-construction-using","title":"Online Vectorized HD Map Construction using Geometry","arxiv_id":"2312.03341","date":"2023-12-06","proceeding":null,"authors":["Zhixin Zhang","Yiyuan Zhang","Xiaohan Ding","Fusheng Jin","Xiangyu Yue"],"abstract":"The construction of online vectorized High-Definition (HD) maps is critical for downstream prediction and planning. Recent efforts have built strong baselines for this task, however, shapes and relations of instances in urban road systems are still under-explored, such as parallelism, perpendicular, or rectangle-shape. In our work, we propose GeMap ($\\textbf{Ge}$ometry $\\textbf{Map}$), which end-to-end learns Euclidean shapes and relations of map instances beyond basic perception. Specifically, we design a geometric loss based on angle and distance clues, which is robust to rigid transformations. We also decouple self-attention to independently handle Euclidean shapes and relations. Our method achieves new state-of-the-art performance on the NuScenes and Argoverse 2 datasets. Remarkably, it reaches a 71.8% mAP on the large-scale Argoverse 2 dataset, outperforming MapTR V2 by +4.4% and surpassing the 70% mAP threshold for the first time. Code is available at https://github.com/cnzzx/GeMap.","url_abs":"https://arxiv.org/abs/2312.03341v2","url_pdf":"https://arxiv.org/pdf/2312.03341v2.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":"online-vectorized-hd-map-construction-using","repo_url":"https://github.com/cnzzx/gemap","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"online-vectorized-hd-map-construction","task_name":"Online Vectorized HD Map Construction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2312.03341","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.03341"}},"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/cnzzx/gemap","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"ran":1,"ran_fixture":1},"by_repo_kind":{"official":{"samples":2,"ran":2,"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":"2e121cd3bb994517","entry":"normalize_2d_pts","repo":"cnzzx/gemap","repo_kind":"official","path":"projects/mmdet3d_plugin/gemap/losses/geo_loss.py","file_url":"https://github.com/cnzzx/gemap/blob/HEAD/projects/mmdet3d_plugin/gemap/losses/geo_loss.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"2e121cd3bb994517"}},{"code_sha256_prefix":"b2b9a1966482ef96","entry":"reduce_loss","repo":"cnzzx/gemap","repo_kind":"official","path":"projects/mmdet3d_plugin/gemap/losses/map_loss.py","file_url":"https://github.com/cnzzx/gemap/blob/HEAD/projects/mmdet3d_plugin/gemap/losses/map_loss.py","link_basis":"harvester_set","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"b2b9a1966482ef96"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}