{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,21]],"date-time":"2025-06-21T06:22:21Z","timestamp":1750486941412,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":39,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,12,1]],"date-time":"2022-12-01T00:00:00Z","timestamp":1669852800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12]]},"DOI":"10.1145\/3565516.3565521","type":"proceedings-article","created":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T17:18:33Z","timestamp":1669137513000},"page":"1-10","source":"Crossref","is-referenced-by-count":7,"title":["Semantic Segmentation for Multi-Contour Estimation in Maritime Scenes"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9620-9866","authenticated-orcid":false,"given":"Alastair","family":"Finlinson","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Surrey, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0164-8322","authenticated-orcid":false,"given":"Sotiris","family":"Moschoyiannis","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Surrey, United Kingdom"}]}],"member":"320","published-online":{"date-parts":[[2022,12]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2019.102879"},{"key":"e_1_3_2_1_2_1","volume-title":"Proceedings of the 2012 9th Conference on Computer and Robot Vision, CRV 2012, 346\u2013352","author":"Boroujeni Nasim","year":"2012","unstructured":"Nasim Boroujeni , Ali Etemad , and A.D. Whitehead . 2012. Robust Horizon Detection Using Segmentation for UAV Applications . Proceedings of the 2012 9th Conference on Computer and Robot Vision, CRV 2012, 346\u2013352 . https:\/\/doi.org\/10.1109\/CRV. 2012 .52 10.1109\/CRV.2012.52 Nasim Boroujeni, Ali Etemad, and A.D. Whitehead. 2012. Robust Horizon Detection Using Segmentation for UAV Applications. Proceedings of the 2012 9th Conference on Computer and Robot Vision, CRV 2012, 346\u2013352. https:\/\/doi.org\/10.1109\/CRV.2012.52"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197194"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967909"},{"key":"e_1_3_2_1_5_1","volume-title":"Albumentations: Fast and Flexible Image Augmentations. Information 11, 2","author":"Buslaev Alexander","year":"2020","unstructured":"Alexander Buslaev , Vladimir\u00a0 I. Iglovikov , Eugene Khvedchenya , Alex Parinov , Mikhail Druzhinin , and Alexandr\u00a0 A. Kalinin . 2020 . Albumentations: Fast and Flexible Image Augmentations. Information 11, 2 (2020). https:\/\/doi.org\/10.3390\/info11020125 10.3390\/info11020125 Alexander Buslaev, Vladimir\u00a0I. Iglovikov, Eugene Khvedchenya, Alex Parinov, Mikhail Druzhinin, and Alexandr\u00a0A. Kalinin. 2020. Albumentations: Fast and Flexible Image Augmentations. Information 11, 2 (2020). https:\/\/doi.org\/10.3390\/info11020125"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13640-017-0240-z"},{"key":"e_1_3_2_1_7_1","volume-title":"Transunet: Transformers make strong encoders for medical image segmentation. arXiv preprint arXiv:2102.04306(2021).","author":"Chen Jieneng","year":"2021","unstructured":"Jieneng Chen , Yongyi Lu , Qihang Yu , Xiangde Luo , Ehsan Adeli , Yan Wang , Le Lu , Alan\u00a0 L Yuille , and Yuyin Zhou . 2021 . Transunet: Transformers make strong encoders for medical image segmentation. arXiv preprint arXiv:2102.04306(2021). Jieneng Chen, Yongyi Lu, Qihang Yu, Xiangde Luo, Ehsan Adeli, Yan Wang, Le Lu, Alan\u00a0L Yuille, and Yuyin Zhou. 2021. Transunet: Transformers make strong encoders for medical image segmentation. arXiv preprint arXiv:2102.04306(2021)."},{"key":"e_1_3_2_1_8_1","volume-title":"Rethinking atrous convolution for semantic image segmentation. arXiv","author":"Chen Liang-Chieh","year":"2017","unstructured":"Liang-Chieh Chen , G Papandreou , F Schroff , and H Adam . 2019. Rethinking atrous convolution for semantic image segmentation. arXiv 2017 . arXiv preprint arXiv:1706.05587(2019). Liang-Chieh Chen, G Papandreou, F Schroff, and H Adam. 2019. Rethinking atrous convolution for semantic image segmentation. arXiv 2017. arXiv preprint arXiv:1706.05587(2019)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00359"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1587\/transinf.2021EDP7064"},{"key":"e_1_3_2_1_12_1","unstructured":"Evgeny Gershikov Tzvika Libe and Samuel Kosolapov. 2013. Horizon line detection in marine images: which method to choose?International Journal on Advances in Intelligent Systems 6 1(2013).  Evgeny Gershikov Tzvika Libe and Samuel Kosolapov. 2013. Horizon line detection in marine images: which method to choose?International Journal on Advances in Intelligent Systems 6 1(2013)."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/rob.21929"},{"key":"#cr-split#-e_1_3_2_1_14_1.1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2015. Deep Residual Learning for Image Recognition. https:\/\/doi.org\/10.48550\/ARXIV.1512.03385 10.48550\/ARXIV.1512.03385"},{"key":"#cr-split#-e_1_3_2_1_14_1.2","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2015. Deep Residual Learning for Image Recognition. https:\/\/doi.org\/10.48550\/ARXIV.1512.03385"},{"key":"#cr-split#-e_1_3_2_1_15_1.1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Identity Mappings in Deep Residual Networks. https:\/\/doi.org\/10.48550\/ARXIV.1603.05027 10.48550\/ARXIV.1603.05027"},{"key":"#cr-split#-e_1_3_2_1_15_1.2","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Identity Mappings in Deep Residual Networks. https:\/\/doi.org\/10.48550\/ARXIV.1603.05027"},{"key":"e_1_3_2_1_16_1","volume-title":"2011 IEEE International Conference on Robotics and Automation. 731\u2013736","author":"K.","year":"2011","unstructured":"Hordur\u00a0 K. Heidarsson and Gaurav\u00a0S. Sukhatme. 2011. Obstacle detection and avoidance for an Autonomous Surface Vehicle using a profiling sonar . In 2011 IEEE International Conference on Robotics and Automation. 731\u2013736 . https:\/\/doi.org\/10.1109\/ICRA. 2011 .5980509 10.1109\/ICRA.2011.5980509 Hordur\u00a0K. Heidarsson and Gaurav\u00a0S. Sukhatme. 2011. Obstacle detection and avoidance for an Autonomous Surface Vehicle using a profiling sonar. In 2011 IEEE International Conference on Robotics and Automation. 731\u2013736. https:\/\/doi.org\/10.1109\/ICRA.2011.5980509"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1177\/1550147718790753"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3097134"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Alex Kendall Vijay Badrinarayanan and Roberto Cipolla. 2016. Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding. arxiv:1511.02680\u00a0[cs.CV]  Alex Kendall Vijay Badrinarayanan and Roberto Cipolla. 2016. Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding. arxiv:1511.02680\u00a0[cs.CV]","DOI":"10.5244\/C.31.57"},{"key":"e_1_3_2_1_20_1","volume-title":"Efficient inference in fully connected crfs with gaussian edge potentials. Advances in neural information processing systems 24","author":"Kr\u00e4henb\u00fchl Philipp","year":"2011","unstructured":"Philipp Kr\u00e4henb\u00fchl and Vladlen Koltun . 2011. Efficient inference in fully connected crfs with gaussian edge potentials. Advances in neural information processing systems 24 ( 2011 ). Philipp Kr\u00e4henb\u00fchl and Vladlen Koltun. 2011. Efficient inference in fully connected crfs with gaussian edge potentials. Advances in neural information processing systems 24 (2011)."},{"key":"e_1_3_2_1_21_1","volume-title":"Fast image-based obstacle detection from unmanned surface vehicles","author":"Kristan Matej","year":"2015","unstructured":"Matej Kristan , Vildana\u00a0Suli\u0107 Kenk , Stanislav Kova\u010di\u010d , and Janez Per\u0161 . 2015. Fast image-based obstacle detection from unmanned surface vehicles . IEEE transactions on cybernetics 46, 3 ( 2015 ), 641\u2013654. Matej Kristan, Vildana\u00a0Suli\u0107 Kenk, Stanislav Kova\u010di\u010d, and Janez Per\u0161. 2015. Fast image-based obstacle detection from unmanned surface vehicles. IEEE transactions on cybernetics 46, 3 (2015), 641\u2013654."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2015.2412251"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32226-7_65"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2019.2893008"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11036-021-01752-2"},{"key":"e_1_3_2_1_26_1","unstructured":"Xiao-Jiao Mao Chunhua Shen and Yu-Bin Yang. 2016. Image restoration using convolutional auto-encoders with symmetric skip connections. arXiv preprint arXiv:1606.08921(2016).  Xiao-Jiao Mao Chunhua Shen and Yu-Bin Yang. 2016. Image restoration using convolutional auto-encoders with symmetric skip connections. arXiv preprint arXiv:1606.08921(2016)."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.23919\/FUSION45008.2020.9190450"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2012.2194473"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.3390\/s18092825"},{"key":"e_1_3_2_1_32_1","volume-title":"International Conference on Machine Learning. PMLR, 6105\u20136114","author":"Tan Mingxing","year":"2019","unstructured":"Mingxing Tan and Quoc Le . 2019 . Efficientnet: Rethinking model scaling for convolutional neural networks . In International Conference on Machine Learning. PMLR, 6105\u20136114 . Mingxing Tan and Quoc Le. 2019. Efficientnet: Rethinking model scaling for convolutional neural networks. In International Conference on Machine Learning. PMLR, 6105\u20136114."},{"key":"e_1_3_2_1_33_1","first-page":"16","article-title":"Visual Horizon Line Detection for UAV","volume":"20","author":"Timotheatos Stavros","year":"2019","unstructured":"Stavros Timotheatos , Stylianos Piperakis , and Panos Trahanias . 2019 . Visual Horizon Line Detection for UAV Navigation. Int. J. Mech. Control 20 (2019), 16 . Stavros Timotheatos, Stylianos Piperakis, and Panos Trahanias. 2019. Visual Horizon Line Detection for UAV Navigation. Int. J. Mech. Control 20(2019), 16.","journal-title":"Navigation. Int. J. Mech. Control"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.3390\/jmse9121329"},{"key":"e_1_3_2_1_35_1","volume-title":"A survey on horizon detection algorithms for maritime video surveillance: advances and future techniques. The Visual Computer","author":"Zardoua Yassir","year":"2021","unstructured":"Yassir Zardoua , Abdelali Astito , and Mohammed Boulaala . 2021. A survey on horizon detection algorithms for maritime video surveillance: advances and future techniques. The Visual Computer ( 2021 ), 1\u201321. Yassir Zardoua, Abdelali Astito, and Mohammed Boulaala. 2021. A survey on horizon detection algorithms for maritime video surveillance: advances and future techniques. The Visual Computer (2021), 1\u201321."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00861"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.3390\/s20061682"}],"event":{"name":"CVMP '22: European Conference on Visual Media Production","sponsor":["SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques"],"location":"London United Kingdom","acronym":"CVMP '22"},"container-title":["European Conference on Visual Media Production"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3565516.3565521","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3565516.3565521","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:48:51Z","timestamp":1750182531000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3565516.3565521"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12]]},"references-count":39,"alternative-id":["10.1145\/3565516.3565521","10.1145\/3565516"],"URL":"https:\/\/doi.org\/10.1145\/3565516.3565521","relation":{},"subject":[],"published":{"date-parts":[[2022,12]]}}}