{"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/long-term-tracking-in-the-wild-a-benchmark","title":"Long-term Tracking in the Wild: A Benchmark","arxiv_id":"1803.09502","date":"2018-03-26","proceeding":"ECCV 2018 9","authors":["Jack Valmadre","Luca Bertinetto","João F. Henriques","Ran Tao","Andrea Vedaldi","Arnold Smeulders","Philip Torr","Efstratios Gavves"],"abstract":"We introduce the OxUvA dataset and benchmark for evaluating single-object\ntracking algorithms. Benchmarks have enabled great strides in the field of\nobject tracking by defining standardized evaluations on large sets of diverse\nvideos. However, these works have focused exclusively on sequences that are\njust tens of seconds in length and in which the target is always visible.\nConsequently, most researchers have designed methods tailored to this\n\"short-term\" scenario, which is poorly representative of practitioners' needs.\nAiming to address this disparity, we compile a long-term, large-scale tracking\ndataset of sequences with average length greater than two minutes and with\nfrequent target object disappearance. The OxUvA dataset is much larger than the\nobject tracking datasets of recent years: it comprises 366 sequences spanning\n14 hours of video. We assess the performance of several algorithms, considering\nboth the ability to locate the target and to determine whether it is present or\nabsent. Our goal is to offer the community a large and diverse benchmark to\nenable the design and evaluation of tracking methods ready to be used \"in the\nwild\". The project website is http://oxuva.net","url_abs":"http://arxiv.org/abs/1803.09502v3","url_pdf":"http://arxiv.org/pdf/1803.09502v3.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":"object","task_name":"Object"},{"task_slug":"object-tracking","task_name":"Object Tracking"}],"methods":[],"datasets_introduced":[{"slug":"oxuva","name":"OxUva","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1803.09502","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}