{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T11:42:09Z","timestamp":1784288529422,"version":"3.55.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>Transformers have been successfully applied to the visual tracking task and significantly promote tracking performance. The self-attention mechanism designed to model long-range dependencies is the key to the success of Transformers. However, self-attention lacks focusing on the most relevant information in the search regions, making it easy to be distracted by background. In this paper, we relieve this issue with a sparse attention mechanism by focusing the most relevant information in the search regions, which enables a much accurate tracking. Furthermore, we introduce a double-head predictor to boost the accuracy of foreground-background classification and regression of target bounding boxes, which further improve the tracking performance. Extensive experiments show that, without bells and whistles, our method significantly outperforms the state-of-the-art approaches on LaSOT, GOT-10k, TrackingNet, and UAV123, while running at 40 FPS. Notably, the training time of our method is reduced by 75% compared to that of TransT. The source code and models are available at https:\/\/github.com\/fzh0917\/SparseTT.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/127","type":"proceedings-article","created":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T02:55:56Z","timestamp":1657940156000},"page":"905-912","source":"Crossref","is-referenced-by-count":153,"title":["SparseTT: Visual Tracking with Sparse Transformers"],"prefix":"10.24963","author":[{"given":"Zhihong","family":"Fu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Virtual Reality Technology and System, Beihang University, Beijing 100191, China"},{"name":"Hangzhou Innovation Institute, Beihang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zehua","family":"Fu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Virtual Reality Technology and System, Beihang University, Beijing 100191, China"},{"name":"Hangzhou Innovation Institute, Beihang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingjie","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Virtual Reality Technology and System, Beihang University, Beijing 100191, China"},{"name":"Hangzhou Innovation Institute, Beihang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenrui","family":"Cai","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Virtual Reality Technology and System, Beihang University, Beijing 100191, China"},{"name":"Hangzhou Innovation Institute, Beihang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunhong","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Virtual Reality Technology and System, Beihang University, Beijing 100191, China"},{"name":"Hangzhou Innovation Institute, Beihang University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","theme":"Artificial Intelligence","location":"Vienna, Austria","acronym":"IJCAI-2022","number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2022,7,23]]},"end":{"date-parts":[[2022,7,29]]}},"container-title":["Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T11:07:51Z","timestamp":1658142471000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/127"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2022\/127","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}