{"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/cilantro-a-lean-versatile-and-efficient","title":"cilantro: A Lean, Versatile, and Efficient Library for Point Cloud Data Processing","arxiv_id":"1807.00399","date":"2018-07-01","proceeding":null,"authors":["Konstantinos Zampogiannis","Cornelia Fermuller","Yiannis Aloimonos"],"abstract":"We introduce cilantro, an open-source C++ library for geometric and\ngeneral-purpose point cloud data processing. The library provides functionality\nthat covers low-level point cloud operations, spatial reasoning, various\nmethods for point cloud segmentation and generic data clustering, flexible\nalgorithms for robust or local geometric alignment, model fitting, as well as\npowerful visualization tools. To accommodate all kinds of workflows, cilantro\nis almost fully templated, and most of its generic algorithms operate in\narbitrary data dimension. At the same time, the library is easy to use and\nhighly expressive, promoting a clean and concise coding style. cilantro is\nhighly optimized, has a minimal set of external dependencies, and supports\nrapid development of performant point cloud processing software in a wide\nvariety of contexts.","url_abs":"http://arxiv.org/abs/1807.00399v3","url_pdf":"http://arxiv.org/pdf/1807.00399v3.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":"cilantro-a-lean-versatile-and-efficient","repo_url":"https://github.com/kzampog/cilantro","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"point-cloud-segmentation","task_name":"Point Cloud Segmentation"},{"task_slug":"spatial-reasoning","task_name":"Spatial Reasoning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}