{"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/autoregressive-visual-tracking","title":"Autoregressive Visual Tracking","arxiv_id":null,"date":"2023-01-01","proceeding":"CVPR 2023 2023 2","authors":["Xing Wei","Yifan Bai","Yongchao Zheng","Dahu Shi","Yihong Gong"],"abstract":"    We present ARTrack, an autoregressive framework for visual object tracking. ARTrack tackles tracking as a coordinate sequence interpretation task that estimates object trajectories progressively, where the current estimate is induced by previous states and in turn affects subsequences. This time-autoregressive approach models the sequential evolution of trajectories to keep tracing the object across frames, making it superior to existing template matching based trackers that only consider the per-frame localization accuracy. ARTrack is simple and direct, eliminating customized localization heads and post-processings. Despite its simplicity, ARTrack achieves state-of-the-art performance on prevailing benchmark datasets.    ","url_abs":"http://openaccess.thecvf.com//content/CVPR2023/html/Wei_Autoregressive_Visual_Tracking_CVPR_2023_paper.html","url_pdf":"http://openaccess.thecvf.com//content/CVPR2023/papers/Wei_Autoregressive_Visual_Tracking_CVPR_2023_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":[{"paper_slug":"autoregressive-visual-tracking","repo_url":"https://github.com/miv-xjtu/artrack","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"object","task_name":"Object"},{"task_slug":"object-tracking","task_name":"Object Tracking"},{"task_slug":"template-matching","task_name":"Template Matching"},{"task_slug":"video-object-tracking","task_name":"Video Object Tracking"},{"task_slug":"visual-object-tracking","task_name":"Visual Object Tracking"},{"task_slug":"visual-tracking","task_name":"Visual Tracking"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/video-object-tracking-on-nv-vot211","task":"Video Object Tracking","dataset":"NT-VOT211","model":"ARTrack-L","rank_in_archive_order":17,"of":43,"metrics":{"AUC":"35.92","Precision":"51.64"},"uses_additional_data":false},{"leaderboard":"/sota/visual-object-tracking-on-got-10k","task":"Visual Object Tracking","dataset":"GOT-10k","model":"ARTrack-L","rank_in_archive_order":9,"of":42,"metrics":{"Average Overlap":"78.5","Success Rate 0.5":"87.4","Success Rate 0.75":"77.8"},"uses_additional_data":false},{"leaderboard":"/sota/visual-object-tracking-on-lasot","task":"Visual Object Tracking","dataset":"LaSOT","model":"ARTrack-L","rank_in_archive_order":16,"of":46,"metrics":{"AUC":"73.1","Normalized Precision":"82.2","Precision":"80.3"},"uses_additional_data":false},{"leaderboard":"/sota/visual-object-tracking-on-lasot-ext","task":"Visual Object Tracking","dataset":"LaSOT-ext","model":"ARTrack-L","rank_in_archive_order":12,"of":18,"metrics":{"AUC":"52.8","Normalized Precision":"62.9","Precision":"59.7"},"uses_additional_data":false},{"leaderboard":"/sota/visual-object-tracking-on-tnl2k","task":"Visual Object Tracking","dataset":"TNL2K","model":"ARTrack-L","rank_in_archive_order":12,"of":16,"metrics":{"AUC":"60.3"},"uses_additional_data":false},{"leaderboard":"/sota/visual-object-tracking-on-trackingnet","task":"Visual Object Tracking","dataset":"TrackingNet","model":"ARTrack-L","rank_in_archive_order":11,"of":40,"metrics":{"Accuracy":"85.6","Normalized Precision":"89.6","Precision":"86.0"},"uses_additional_data":false},{"leaderboard":"/sota/visual-object-tracking-on-uav123","task":"Visual Object Tracking","dataset":"UAV123","model":"ARTrack-L","rank_in_archive_order":6,"of":16,"metrics":{"AUC":"0.712"},"uses_additional_data":false},{"leaderboard":"/sota/visual-tracking-on-tnl2k","task":"Visual Tracking","dataset":"TNL2K","model":"ARTrack-L","rank_in_archive_order":1,"of":6,"metrics":{"AUC":"60.3"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}