{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:23:42Z","timestamp":1750220622919,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Guangdong Basic and Applied Basic Research Foundation","award":["2020B1515020048"],"award-info":[{"award-number":["2020B1515020048"]}]},{"name":"State Key Development Program","award":["2016YFB1001004"],"award-info":[{"award-number":["2016YFB1001004"]}]},{"name":"National Natural Science Foundation of China","award":["61976250"],"award-info":[{"award-number":["61976250"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,10,12]]},"DOI":"10.1145\/3394171.3416279","type":"proceedings-article","created":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T12:26:25Z","timestamp":1602505585000},"page":"4669-4673","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Modularized Framework with Category-Sensitive Abnormal Filter for City Anomaly Detection"],"prefix":"10.1145","author":[{"given":"Jie","family":"Wu","sequence":"first","affiliation":[{"name":"Sun Yat-sen University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingying","family":"Li","sequence":"additional","affiliation":[{"name":"Baidu Inc., Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Baidu Inc., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Wu","sequence":"additional","affiliation":[{"name":"Energy Development Research Institute, China Southern Power Grid, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Tan","sequence":"additional","affiliation":[{"name":"Baidu Inc., Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongwu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Baidu Inc., Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shilei","family":"Wen","sequence":"additional","affiliation":[{"name":"Baidu Inc., Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Errui","family":"Ding","sequence":"additional","affiliation":[{"name":"Baidu Inc., Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanbin","family":"Li","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.502"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995434"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.86"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459342"},{"key":"e_1_3_2_2_5_1","volume-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167","author":"Ioffe Sergey","year":"2015","unstructured":"Sergey Ioffe and Christian Szegedy . 2015. Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167 ( 2015 ). Sergey Ioffe and Christian Szegedy. 2015. Batch normalization: Accelerating deep network training by reducing internal covariate shift. arXiv preprint arXiv:1502.03167 (2015)."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206569"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206771"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00301"},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00718"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.338"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.45"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/AVSS.2014.6918692"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00015"},{"key":"e_1_3_2_2_14_1","volume-title":"CVPR Workshops.","author":"Naphade Milind","year":"2019","unstructured":"Milind Naphade , Zheng Tang , Ming-Ching Chang , David C Anastasiu , Anuj Sharma , Rama Chellappa , Shuo Wang , Pranamesh Chakraborty , Tingting Huang , Jenq-Neng Hwang , 2019 . The 2019 ai city challenge . In CVPR Workshops. Milind Naphade, Zheng Tang, Ming-Ching Chang, David C Anastasiu, Anuj Sharma, Rama Chellappa, Shuo Wang, Pranamesh Chakraborty, Tingting Huang, Jenq-Neng Hwang, et al. 2019. The 2019 ai city challenge. In CVPR Workshops."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00678"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46484-8_2"},{"key":"e_1_3_2_2_17_1","volume-title":"Tree-Structured Policy based Progressive Reinforcement Learning for Temporally Language Grounding in Video. arXiv preprint arXiv:2001.06680","author":"Wu Jie","year":"2020","unstructured":"Jie Wu , Guanbin Li , Si Liu , and Liang Lin . 2020. Tree-Structured Policy based Progressive Reinforcement Learning for Temporally Language Grounding in Video. arXiv preprint arXiv:2001.06680 ( 2020 ). Jie Wu, Guanbin Li, Si Liu, and Liang Lin. 2020. Tree-Structured Policy based Progressive Reinforcement Learning for Temporally Language Grounding in Video. arXiv preprint arXiv:2001.06680 (2020)."},{"key":"e_1_3_2_2_18_1","volume-title":"Learning deep representations of appearance and motion for anomalous event detection. arXiv preprint arXiv:1510.01553","author":"Xu Dan","year":"2015","unstructured":"Dan Xu , Elisa Ricci , Yan Yan , Jingkuan Song , and Nicu Sebe . 2015. Learning deep representations of appearance and motion for anomalous event detection. arXiv preprint arXiv:1510.01553 ( 2015 ). Dan Xu, Elisa Ricci, Yan Yan, Jingkuan Song, and Nicu Sebe. 2015. Learning deep representations of appearance and motion for anomalous event detection. arXiv preprint arXiv:1510.01553 (2015)."},{"key":"e_1_3_2_2_19_1","volume-title":"Temporal Convolutional Network with Complementary Inner Bag Loss for Weakly Supervised Anomaly Detection. In IEEE International Conference on Image Processing. IEEE, 4030--4034","author":"Zhang Jiangong","year":"2019","unstructured":"Jiangong Zhang , Laiyun Qing , and Jun Miao . 2019 . Temporal Convolutional Network with Complementary Inner Bag Loss for Weakly Supervised Anomaly Detection. In IEEE International Conference on Image Processing. IEEE, 4030--4034 . Jiangong Zhang, Laiyun Qing, and Jun Miao. 2019. Temporal Convolutional Network with Complementary Inner Bag Loss for Weakly Supervised Anomaly Detection. In IEEE International Conference on Image Processing. IEEE, 4030--4034."},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995524"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00133"},{"key":"e_1_3_2_2_22_1","author":"Zhu Yi","year":"2019","unstructured":"Yi Zhu and Shawn Newsam. 2019 . Motion-Aware Feature for Improved Video Anomaly Detection. arXiv preprint arXiv:1907.10211 (2019). Yi Zhu and Shawn Newsam. 2019. Motion-Aware Feature for Improved Video Anomaly Detection. arXiv preprint arXiv:1907.10211 (2019).","journal-title":"Newsam."}],"event":{"name":"MM '20: The 28th ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Seattle WA USA","acronym":"MM '20"},"container-title":["Proceedings of the 28th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3416279","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394171.3416279","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:01:24Z","timestamp":1750197684000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394171.3416279"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,12]]},"references-count":22,"alternative-id":["10.1145\/3394171.3416279","10.1145\/3394171"],"URL":"https:\/\/doi.org\/10.1145\/3394171.3416279","relation":{},"subject":[],"published":{"date-parts":[[2020,10,12]]},"assertion":[{"value":"2020-10-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}