{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T16:55:37Z","timestamp":1777568137392,"version":"3.51.4"},"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":[[2022,7]]},"abstract":"<jats:p>Automatic video polyp segmentation (VPS) is highly valued for the early diagnosis of colorectal cancer. However, existing methods are limited in three respects: 1) most of them work on static images, while ignoring the temporal information in consecutive video frames; 2) all of them are fully supervised and easily overfit in presence of limited annotations; 3) the context of polyp (i.e., lumen, specularity and mucosa tissue) varies in an endoscopic clip, which may affect the predictions of adjacent frames. To resolve these challenges, we propose a novel Temporally Consistent Context-Free Network (TCCNet) for semi-supervised VPS. It contains a segmentation branch and a propagation branch with a co-training scheme to supervise the predictions of unlabeled image. To maintain the temporal consistency of predictions, we design a Sequence-Corrected Reverse Attention module and a Propagation-Corrected Reverse Attention module. A Context-Free Loss is also proposed to mitigate the impact of varying contexts. Extensive experiments show that even trained under 1\/15 label ratio, TCCNet is comparable to the state-of-the-art fully supervised methods for VPS. Also, TCCNet surpasses existing semi-supervised methods for natural image and other medical image segmentation tasks.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/155","type":"proceedings-article","created":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T22:55:56Z","timestamp":1657925756000},"page":"1109-1115","source":"Crossref","is-referenced-by-count":9,"title":["TCCNet: Temporally Consistent Context-Free Network for Semi-supervised Video Polyp Segmentation"],"prefix":"10.24963","author":[{"given":"Xiaotong","family":"Li","sequence":"first","affiliation":[{"name":"Fudan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jilan","family":"Xu","sequence":"additional","affiliation":[{"name":"Fudan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuejie","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fudan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Feng","sequence":"additional","affiliation":[{"name":"Fudan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui-Wei","family":"Zhao","sequence":"additional","affiliation":[{"name":"Fudan University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai University of Finance and Economics"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuequan","family":"Lu","sequence":"additional","affiliation":[{"name":"Deakin University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shang","family":"Gao","sequence":"additional","affiliation":[{"name":"Deakin University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","theme":"Artificial Intelligence","location":"Vienna, Austria","acronym":"IJCAI-2022","number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2022,7,23]]},"end":{"date-parts":[[2022,7,29]]}},"container-title":["Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T07:08:01Z","timestamp":1658128081000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/155"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2022\/155","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}