{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T15:11:11Z","timestamp":1761664271230,"version":"3.37.3"},"reference-count":17,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,7,5]],"date-time":"2021-07-05T00:00:00Z","timestamp":1625443200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,5]],"date-time":"2021-07-05T00:00:00Z","timestamp":1625443200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100007219","name":"Natural Science Foundation of Shanghai","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007219","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,5]]},"DOI":"10.1109\/icme51207.2021.9428159","type":"proceedings-article","created":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T21:14:21Z","timestamp":1623273261000},"page":"1-6","source":"Crossref","is-referenced-by-count":5,"title":["Leveraging Intra-Domain Knowledge to Strengthen Cross-Domain Crowd Counting"],"prefix":"10.1109","author":[{"given":"Yiqing","family":"Cai","sequence":"first","affiliation":[{"name":"East China Normal University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lianggangxu","family":"Chen","sequence":"additional","affiliation":[{"name":"East China Normal University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenwei","family":"Ma","sequence":"additional","affiliation":[{"name":"The Third Research Institute Of Ministry Of Public Security"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changhong","family":"Lu","sequence":"additional","affiliation":[{"name":"East China Normal University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changbo","family":"Wang","sequence":"additional","affiliation":[{"name":"East China Normal University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gaoqi","family":"He","sequence":"additional","affiliation":[{"name":"East China Normal University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.70"},{"key":"ref11","first-page":"2547","article-title":"Multi-source multi-scale counting in extremely dense crowd images","author":"idrees","year":"2013","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref12","first-page":"532","article-title":"Composition loss for counting, density map estimation and localization in dense crowds","author":"idrees","year":"2018","journal-title":"Proceedings of the European Conference on Computer Vision (ECCV)"},{"key":"ref13","first-page":"4031","article-title":"Switching convolutional neural network for crowd counting","author":"babu sam","year":"2017","journal-title":"2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00550"},{"key":"ref15","first-page":"3618","article-title":"Divide and grow: Capturing huge diversity in crowd images with incrementally growing cnn","author":"babu sam","year":"2018","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00524"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00745"},{"article-title":"Feature-aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance","year":"2019","author":"gao","key":"ref3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01302"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2899857"},{"key":"ref8","first-page":"1091","article-title":"Csrnet: Dilated convolutional neural networks for understanding the highly congested scenes","author":"li","year":"2018","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2019.00041"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9054768"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00839"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00780"}],"event":{"name":"2021 IEEE International Conference on Multimedia and Expo (ICME)","start":{"date-parts":[[2021,7,5]]},"location":"Shenzhen, China","end":{"date-parts":[[2021,7,9]]}},"container-title":["2021 IEEE International Conference on Multimedia and Expo (ICME)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9428049\/9428068\/09428159.pdf?arnumber=9428159","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T21:27:40Z","timestamp":1656365260000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9428159\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,5]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1109\/icme51207.2021.9428159","relation":{},"subject":[],"published":{"date-parts":[[2021,7,5]]}}}