乐胖代购免代理版

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Consequently, the detection of video frames will lead to a decline in accuracy by using the image object detection model. This paper proposes an online video object detection method based on the one\u2010stage detector YOLOx. First, the module for space\u2013time feature aggregation is given, which uses the space\u2013time information of past frames to enhance the feature quality of the current frame. Then, the module for result reuse is given, which incorporates the detection results of past frames to improve the detection stability of the current frame. By these two modules, the trade\u2010off between accuracy and speed of video object detection could be achieved. Experimental results on the ImageNet VID show the improvement of speed and accuracy of the proposed\u00a0method.<\/jats:p>","DOI":"10.1049\/ipr2.13179","type":"journal-article","created":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T09:41:52Z","timestamp":1721209312000},"page":"3356-3367","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Video object detection via space\u2013time feature aggregation and result reuse"],"prefix":"10.1049","volume":"18","author":[{"given":"Liang","family":"Duan","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering Yunnan University Kunming China"},{"name":"Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China"}]},{"given":"Rongfei","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering Yunnan University Kunming China"},{"name":"Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-3641-1461","authenticated-orcid":false,"given":"Kun","family":"Yue","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering Yunnan University Kunming China"},{"name":"Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China"}]},{"given":"Zhengbao","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Engineering Yunnan University Kunming China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-8449-6861","authenticated-orcid":false,"given":"Guowu","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering Yunnan University Kunming China"},{"name":"Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China"}]}],"member":"265","published-online":{"date-parts":[[2024,7,17]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1049\/ipr2.12714"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s44196-023-00256-z"},{"key":"e_1_2_10_4_1","first-page":"497","article-title":"A feature temporal attention based interleaved network for fast video object detection","volume":"4","author":"Yang Y.","year":"2021","journal-title":"J. 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