{"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/3dfeat-net-weakly-supervised-local-3d","title":"3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration","arxiv_id":"1807.09413","date":"2018-07-25","proceeding":"ECCV 2018 9","authors":["Zi Jian Yew","Gim Hee Lee"],"abstract":"In this paper, we propose the 3DFeat-Net which learns both 3D feature\ndetector and descriptor for point cloud matching using weak supervision. Unlike\nmany existing works, we do not require manual annotation of matching point\nclusters. Instead, we leverage on alignment and attention mechanisms to learn\nfeature correspondences from GPS/INS tagged 3D point clouds without explicitly\nspecifying them. We create training and benchmark outdoor Lidar datasets, and\nexperiments show that 3DFeat-Net obtains state-of-the-art performance on these\ngravity-aligned datasets.","url_abs":"http://arxiv.org/abs/1807.09413v1","url_pdf":"http://arxiv.org/pdf/1807.09413v1.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":"3dfeat-net-weakly-supervised-local-3d","repo_url":"https://github.com/yewzijian/3DFeatNet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"point-cloud-registration","task_name":"Point Cloud Registration"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/point-cloud-registration-on-kitti","task":"Point Cloud Registration","dataset":"KITTI","model":"3DFeat-Net","rank_in_archive_order":6,"of":6,"metrics":{"Success Rate":"95.97"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1807.09413","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1807.09413"}},"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. 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