{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T13:14:26Z","timestamp":1787318066937,"version":"build-2736575974"},"reference-count":67,"publisher":"Association for Computing Machinery (ACM)","issue":"6","license":[{"start":{"date-parts":[[2024,3,8]],"date-time":"2024-03-08T00:00:00Z","timestamp":1709856000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Key R&D Program of Zhejiang Province, China","award":["2023C01043, 2021C01119"],"award-info":[{"award-number":["2023C01043, 2021C01119"]}]},{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"crossref","award":["62002320, U19B2043"],"award-info":[{"award-number":["62002320, U19B2043"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Science and Technology Innovation 2025 Major Project of Ningbo, China","award":["2023Z236"],"award-info":[{"award-number":["2023Z236"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2024,6,30]]},"abstract":"<jats:p>\n                    Few-Shot Segmentation (FSS) poses significant challenges due to limited support images and large intra-class appearance discrepancies. Most existing approaches focus on aligning the support-query correlations from the same layer of the frozen backbone while neglecting the bias between different tasks and different layers. In this article, we propose a Multi-Content Interaction Network (MCINet) to remedy these issues by fully exploiting and interacting with the different contextual information contained in distinct branches. Specifically, MCINet improves FSS from three perspectives: (1) boosting the query representations through incorporating the independent information from another learnable branch into the features from the frozen backbone, (2) enhancing the support-query correlations by exploiting both the same-layer and adjacent-layer features, and (3) refining the predicted results with a multi-scale mask prediction strategy. Experiments on three benchmarks demonstrate that our approach reaches state-of-the-art performances and outperforms the best competitors with many desirable advantages, especially on the challenging COCO dataset. Code will be released on GitHub (\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/chenhao-zju\/mcinet\">https:\/\/github.com\/chenhao-zju\/mcinet<\/jats:ext-link>\n                    ).\n                  <\/jats:p>","DOI":"10.1145\/3643850","type":"journal-article","created":{"date-parts":[[2024,2,3]],"date-time":"2024-02-03T06:45:12Z","timestamp":1706942712000},"page":"1-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Multi-Content Interaction Network for Few-Shot Segmentation"],"prefix":"10.1145","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5700-1202","authenticated-orcid":false,"given":"Hao","family":"Chen","sequence":"first","affiliation":[{"name":"Zhejiang University, HangZhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0294-2099","authenticated-orcid":false,"given":"Yunlong","family":"Yu","sequence":"additional","affiliation":[{"name":"Zhejiang University, HangZhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0866-0663","authenticated-orcid":false,"given":"Yonghan","family":"Dong","sequence":"additional","affiliation":[{"name":"Huawei Technologies Ltd., ShenZhen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1785-7847","authenticated-orcid":false,"given":"Zheming","family":"Lu","sequence":"additional","affiliation":[{"name":"Zhejiang University, HangZhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6859-9038","authenticated-orcid":false,"given":"Yingming","family":"Li","sequence":"additional","affiliation":[{"name":"Zhejiang University, HangZhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5098-2506","authenticated-orcid":false,"given":"Zhongfei","family":"Zhang","sequence":"additional","affiliation":[{"name":"State University of New York, Binghamton, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,3,8]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01376"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2023.3340740"},{"key":"e_1_3_2_4_2","first-page":"978","volume-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV \u201924)","author":"Chen Hao","year":"2024","unstructured":"Hao Chen, Yonghan Dong, Zheming Lu, Yunlong Yu, and Jungong Han. 2024. 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