{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:35:42Z","timestamp":1723016142058},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,8]]},"abstract":"Glass-like objects are widespread in daily life but remain intractable to be segmented for most existing methods. The transparent property makes it difficult to be distinguished from background, while the tiny separation boundary further impedes the acquisition of their exact contour. In this paper, by revealing the key co-evolution demand of semantic and boundary learning, we propose a Selective Mutual Evolution (SME) module to enable the reciprocal feature learning between them. Then to exploit the global shape context, we propose a Structurally Attentive Refinement (SAR) module to conduct a fine-grained feature refinement for those ambiguous points around the boundary. Finally, to further utilize the multi-scale representation, we integrate the above two modules into a cascaded structure and then introduce a Reciprocal Feature Evolution Network (RFENet) for effective glass-like object segmentation. Extensive experiments demonstrate that our RFENet achieves state-of-the-art performance on three popular public datasets. Code is available at https:\/\/github.com\/VankouF\/RFENet.<\/jats:p>","DOI":"10.24963\/ijcai.2023\/80","type":"proceedings-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:31:30Z","timestamp":1691742690000},"page":"717-725","source":"Crossref","is-referenced-by-count":2,"title":["RFENet: Towards Reciprocal Feature Evolution for Glass Segmentation"],"prefix":"10.24963","author":[{"given":"Ke","family":"Fan","sequence":"first","affiliation":[{"name":"Shanghai Jiao Tong University"}]},{"given":"Changan","family":"Wang","sequence":"additional","affiliation":[{"name":"Tencent Youtu Lab"}]},{"given":"Yabiao","family":"Wang","sequence":"additional","affiliation":[{"name":"Tencent Youtu Lab"}]},{"given":"Chengjie","family":"Wang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University"},{"name":"Tencent Youtu Lab"}]},{"given":"Ran","family":"Yi","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University"}]},{"given":"Lizhuang","family":"Ma","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University"}]}],"member":"10584","event":{"number":"32","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2023","name":"Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}","start":{"date-parts":[[2023,8,19]]},"theme":"Artificial Intelligence","location":"Macau, SAR China","end":{"date-parts":[[2023,8,25]]}},"container-title":["Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:34:14Z","timestamp":1691742854000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2023\/80"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2023\/80","relation":{},"subject":[],"published":{"date-parts":[[2023,8]]}}}