{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T22:33:24Z","timestamp":1768343604575,"version":"3.49.0"},"reference-count":58,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,9]],"date-time":"2022-08-09T00:00:00Z","timestamp":1660003200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["61571394"],"award-info":[{"award-number":["61571394"]}]},{"name":"National Natural Science Foundation of China","award":["62001149"],"award-info":[{"award-number":["62001149"]}]},{"name":"National Natural Science Foundation of China","award":["2020C03098"],"award-info":[{"award-number":["2020C03098"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["61571394"],"award-info":[{"award-number":["61571394"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["62001149"],"award-info":[{"award-number":["62001149"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["2020C03098"],"award-info":[{"award-number":["2020C03098"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Multiple object tracking (MOT) in unmanned aerial vehicle (UAV) videos is a fundamental task and can be applied in many fields. MOT consists of two critical procedures, i.e., object detection and re-identification (ReID). One-shot MOT, which incorporates detection and ReID in a unified network, has gained attention due to its fast inference speed. It significantly reduces the computational overhead by making two subtasks share features. However, most existing one-shot trackers struggle to achieve robust tracking in UAV videos. We observe that the essential difference between detection and ReID leads to an optimization contradiction within one-shot networks. To alleviate this contradiction, we propose a novel feature decoupling network (FDN) to convert shared features into detection-specific and ReID-specific representations. The FDN searches for characteristics and commonalities between the two tasks to synergize detection and ReID. In addition, existing one-shot trackers struggle to locate small targets in UAV videos. Therefore, we design a pyramid transformer encoder (PTE) to enrich the semantic information of the resulting detection-specific representations. By learning scale-aware fine-grained features, the PTE empowers our tracker to locate targets in UAV videos accurately. Extensive experiments on VisDrone2021 and UAVDT benchmarks demonstrate that our tracker achieves state-of-the-art tracking performance.<\/jats:p>","DOI":"10.3390\/rs14163853","type":"journal-article","created":{"date-parts":[[2022,8,10]],"date-time":"2022-08-10T04:20:32Z","timestamp":1660105232000},"page":"3853","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["One-Shot Multiple Object Tracking in UAV Videos Using Task-Specific Fine-Grained Features"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3549-1340","authenticated-orcid":false,"given":"Han","family":"Wu","sequence":"first","affiliation":[{"name":"The School of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Jiahao","family":"Nie","sequence":"additional","affiliation":[{"name":"The School of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7264-2019","authenticated-orcid":false,"given":"Zhiwei","family":"He","sequence":"additional","affiliation":[{"name":"The School of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China"},{"name":"Zhejiang Province Key Laboratory of Equipment Electronics, Hangzhou 310009, China"}]},{"given":"Ziming","family":"Zhu","sequence":"additional","affiliation":[{"name":"The School of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China"}]},{"given":"Mingyu","family":"Gao","sequence":"additional","affiliation":[{"name":"The School of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China"},{"name":"Zhejiang Province Key Laboratory of Equipment Electronics, Hangzhou 310009, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2146","DOI":"10.1109\/TPAMI.2018.2849374","article-title":"On Detection, Data Association and Segmentation for Multi-Target Tracking","volume":"41","author":"Tian","year":"2019","journal-title":"IEEE Trans. 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