{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:13:42Z","timestamp":1750220022217,"version":"3.41.0"},"reference-count":78,"publisher":"Association for Computing Machinery (ACM)","issue":"2s","license":[{"start":{"date-parts":[[2023,2,17]],"date-time":"2023-02-17T00:00:00Z","timestamp":1676592000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2022ZD0210500\/ 2021ZD0112400"],"award-info":[{"award-number":["2022ZD0210500\/ 2021ZD0112400"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61972067\/U21A20491\/U1908214"],"award-info":[{"award-number":["61972067\/U21A20491\/U1908214"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Innovation Technology Funding of Dalian","award":["2020JJ26GX036"],"award-info":[{"award-number":["2020JJ26GX036"]}]},{"name":"Research Grants Council of Hong Kong","award":["11205620"],"award-info":[{"award-number":["11205620"]}]},{"name":"Strategic Research Grant from City University of Hong Kong","award":["7005674"],"award-info":[{"award-number":["7005674"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2023,6,30]]},"abstract":"<jats:p>\n            Mirrors are everywhere in our daily lives. Existing computer vision systems do not consider mirrors, and hence may get confused by the reflected content inside a mirror, resulting in a severe performance degradation. However, separating the real content outside a mirror from the reflected content inside it is non-trivial. The key challenge is that mirrors typically reflect contents similar to their surroundings, making it very difficult to differentiate the two. In this article, we present a novel method to segment mirrors from a single RGB image. To the best of our knowledge, this is the first work to address the mirror segmentation problem with a computational approach. We make the following contributions: First, we propose a novel network, called MirrorNet+, for mirror segmentation, by modeling both contextual contrasts and semantic associations. Second, we construct the first large-scale mirror segmentation dataset, which consists of 4,018 pairs of images containing mirrors and their corresponding manually annotated mirror masks, covering a variety of daily-life scenes. Third, we conduct extensive experiments to evaluate the proposed method and show that it outperforms the related state-of-the-art detection and segmentation methods. Fourth, we further validate the effectiveness and generalization capability of the proposed semantic awareness contextual contrasted feature learning by applying MirrorNet+ to other vision tasks, i.e., salient object detection and shadow detection. Finally, we provide some applications of mirror segmentation and analyze possible future research directions. Project homepage:\n            <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/mhaiyang.github.io\/TOMM2022-MirrorNet+\/index.html\">https:\/\/mhaiyang.github.io\/TOMM2022-MirrorNet+\/index.html<\/jats:ext-link>\n            .\n          <\/jats:p>","DOI":"10.1145\/3566127","type":"journal-article","created":{"date-parts":[[2022,11,5]],"date-time":"2022-11-05T11:29:45Z","timestamp":1667647785000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Mirror Segmentation via Semantic-aware Contextual Contrasted Feature Learning"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3549-9684","authenticated-orcid":false,"given":"Haiyang","family":"Mei","sequence":"first","affiliation":[{"name":"Dalian University of Technology, Dalian City, Liaoning Province, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5347-8687","authenticated-orcid":false,"given":"Letian","family":"Yu","sequence":"additional","affiliation":[{"name":"Dalian University of Technology, Dalian City, Liaoning Province, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5855-3810","authenticated-orcid":false,"given":"Ke","family":"Xu","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Kowloon, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3369-6772","authenticated-orcid":false,"given":"Yang","family":"Wang","sequence":"additional","affiliation":[{"name":"Dalian University of Technology, Dalian City, Liaoning Province, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8046-722X","authenticated-orcid":false,"given":"Xin","family":"Yang","sequence":"additional","affiliation":[{"name":"Dalian University of Technology, Dalian City, Liaoning Province, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8497-611X","authenticated-orcid":false,"given":"Xiaopeng","family":"Wei","sequence":"additional","affiliation":[{"name":"Dalian University of Technology, Dalian City, Liaoning Province, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8957-8129","authenticated-orcid":false,"given":"Rynson W. 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