{"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/learning-local-feature-descriptors-for","title":"Learning Local Feature Descriptors for Multiple Object Tracking","arxiv_id":null,"date":"2020-11-20","proceeding":null,"authors":["Dmytro Mykheievskyi","Dmytro Borysenko","Viktor Porokhonskyy"],"abstract":"The present study aims at learning class-agnostic embedding, which is suitable for Multiple Object Tracking (MOT). We demonstrate that the learning of local feature descriptors could provide a sufficient level of generalization. Proposed embedding function exhibits on-par performance with its dedicated person re-identification counterparts in their target domain and outperforms them in others. Through its utilization, our solutions achieve state-of-the-art performance in a number of MOT benchmarks, which includes CVPR'19 Tracking Challenge.","url_abs":"https://openaccess.thecvf.com/content/ACCV2020/html/Mykheievskyi_Learning_Local_Feature_Descriptors_for_Multiple_Object_Tracking_ACCV_2020_paper.html","url_pdf":"https://openaccess.thecvf.com/content/ACCV2020/papers/Mykheievskyi_Learning_Local_Feature_Descriptors_for_Multiple_Object_Tracking_ACCV_2020_paper.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":[],"tasks":[{"task_slug":"multiple-object-tracking","task_name":"Multiple Object Tracking"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-tracking","task_name":"Object Tracking"},{"task_slug":"person-re-identification","task_name":"Person Re-Identification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/multiple-object-tracking-on-kitti-test-online","task":"Multiple Object Tracking","dataset":"KITTI Test (Online Methods)","model":"SRK ODESA","rank_in_archive_order":20,"of":34,"metrics":{"MOTA":"90.03"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}