{"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/pcan-3d-attention-map-learning-using","title":"PCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval","arxiv_id":"1904.09793","date":"2019-04-22","proceeding":"CVPR 2019 6","authors":["Wenxiao Zhang","Chunxia Xiao"],"abstract":"Point cloud based retrieval for place recognition is an emerging problem in\nvision field. The main challenge is how to find an efficient way to encode the\nlocal features into a discriminative global descriptor. In this paper, we\npropose a Point Contextual Attention Network (PCAN), which can predict the\nsignificance of each local point feature based on point context. Our network\nmakes it possible to pay more attention to the task-relevent features when\naggregating local features. Experiments on various benchmark datasets show that\nthe proposed network can provide outperformance than current state-of-the-art\napproaches.","url_abs":"http://arxiv.org/abs/1904.09793v1","url_pdf":"http://arxiv.org/pdf/1904.09793v1.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":"pcan-3d-attention-map-learning-using","repo_url":"https://github.com/XLechter/PCAN","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"3d-place-recognition","task_name":"3D Place Recognition"},{"task_slug":null,"task_name":"Point Cloud Retrieval"},{"task_slug":"retrieval","task_name":"Retrieval"},{"task_slug":"visual-place-recognition","task_name":"Visual Place Recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/3d-place-recognition-on-oxford-robotcar","task":"3D Place Recognition","dataset":"Oxford RobotCar Dataset","model":"PCAN","rank_in_archive_order":9,"of":10,"metrics":{"AR@1%":"83.8"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1904.09793","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}