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In NeurIPS, Vol. 33."},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2983686"},{"key":"e_1_3_2_2_42_1","volume-title":"STNet: Scale Tree Network with Multi-level Auxiliator for Crowd Counting. TMM","author":"Wang Mingjie","year":"2022","unstructured":"Mingjie Wang , Hao Cai , Xianfeng Han , Jun Zhou , and Minglun Gong . 2022. STNet: Scale Tree Network with Multi-level Auxiliator for Crowd Counting. TMM ( 2022 ), 1--9. Mingjie Wang, Hao Cai, Xianfeng Han, Jun Zhou, and Minglun Gong. 2022. STNet: Scale Tree Network with Multi-level Auxiliator for Crowd Counting. TMM (2022), 1--9."},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3013269"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3055632"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"crossref","unstructured":"Yi Wang Xinyu Hou and Lap-Pui Chau. 2021. Dense Point Prediction: A Simple Baseline for Crowd Counting and Localization. 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Objects as points. arXiv:1904.07850 (2019)."}],"event":{"name":"MM '22: The 30th ACM International Conference on Multimedia","location":"Lisboa Portugal","acronym":"MM '22","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 30th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3503161.3547863","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3503161.3547863","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:02:35Z","timestamp":1750186955000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3503161.3547863"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,10]]},"references-count":54,"alternative-id":["10.1145\/3503161.3547863","10.1145\/3503161"],"URL":"https:\/\/doi.org\/10.1145\/3503161.3547863","relation":{},"subject":[],"published":{"date-parts":[[2022,10,10]]},"assertion":[{"value":"2022-10-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}