{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:25:55Z","timestamp":1750220755389,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":29,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,4,23]],"date-time":"2020-04-23T00:00:00Z","timestamp":1587600000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,4,23]]},"DOI":"10.1145\/3404555.3404624","type":"proceedings-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T17:00:58Z","timestamp":1597942858000},"page":"182-187","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Auxiliary Edge Detection for Semantic Image Segmentation"],"prefix":"10.1145","author":[{"given":"Wenrui","family":"Liu","sequence":"first","affiliation":[{"name":"Tsinghua Shenzhen International, Graduate School"}]},{"given":"Zongqing","family":"Lu","sequence":"additional","affiliation":[{"name":"Tsinghua Shenzhen International, Graduate School"}]},{"given":"He","family":"Xu","sequence":"additional","affiliation":[{"name":"Tsinghua Shenzhen International, Graduate School"}]}],"member":"320","published-online":{"date-parts":[[2020,8,20]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"3213","article-title":"The cityscapes dataset for semantic urban scene understanding","author":"Cordts M","year":"2016","unstructured":"M Cordts , M Omran , S Ramos , T Rehfeld , M Enzweiler , R Benenson , U Franke , S Roth , and B Schiele , \" The cityscapes dataset for semantic urban scene understanding ,\" in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016 , pp. 3213 -- 3223 . M Cordts, M Omran, S Ramos, T Rehfeld, M Enzweiler, R Benenson, U Franke, S Roth, and B Schiele, \"The cityscapes dataset for semantic urban scene understanding,\" in Proceedings of the IEEE conference on computer vision and pattern recognition, 2016, pp. 3213--3223.","journal-title":"Proceedings of the IEEE conference on computer vision and pattern recognition"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"e_1_3_2_1_3_1","first-page":"3431","article-title":"Fully convolutional networks for semantic segmentation","author":"Long J","year":"2015","unstructured":"J Long , E Shelhamer , and T Darrell , \" Fully convolutional networks for semantic segmentation ,\" in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015 , pp. 3431 -- 3440 . J Long, E Shelhamer, and T Darrell, \"Fully convolutional networks for semantic segmentation,\" in Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 3431--3440.","journal-title":"Proceedings of the IEEE conference on computer vision and pattern recognition"},{"key":"e_1_3_2_1_4_1","first-page":"1269","volume-title":"IEEE","author":"Xing FZ","year":"2016","unstructured":"FZ Xing , E Cambria , W Huang , and Y Xu , \"Weakly supervised semantic segmentation with superpixel embedding,\"in 2016 IEEE International Conference on Image Processing (ICIP) . IEEE , 2016 , pp. 1269 -- 1273 . FZ Xing, E Cambria, W Huang, and Y Xu, \"Weakly supervised semantic segmentation with superpixel embedding,\"in 2016 IEEE International Conference on Image Processing (ICIP). IEEE, 2016, pp. 1269--1273."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.179"},{"volume-title":"Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,\" IEEE transactions on pattern analysis and machine intelligence","author":"Chen L","key":"e_1_3_2_1_6_1","unstructured":"L Chen , G Papandreou , I Kokkinos , K Murphy , and AL Yuille , \"Deeplab : Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,\" IEEE transactions on pattern analysis and machine intelligence , vol. 40 , no. 4, pp. 834--848, 2017. L Chen, G Papandreou, I Kokkinos, K Murphy, and AL Yuille, \"Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,\" IEEE transactions on pattern analysis and machine intelligence, vol. 40, no. 4, pp. 834--848, 2017."},{"volume-title":"A deep convolutional encoder-decoder architecture for image segmentation,\" IEEE transactions on pattern analysis and machine intelligence","author":"Badrinarayanan V","key":"e_1_3_2_1_7_1","unstructured":"V Badrinarayanan , A Kendall , and R Cipolla , \"Segnet : A deep convolutional encoder-decoder architecture for image segmentation,\" IEEE transactions on pattern analysis and machine intelligence , vol. 39 , no. 12, pp. 2481--2495, 2017. V Badrinarayanan, A Kendall, and R Cipolla, \"Segnet: A deep convolutional encoder-decoder architecture for image segmentation,\" IEEE transactions on pattern analysis and machine intelligence, vol. 39, no. 12, pp. 2481--2495, 2017."},{"key":"e_1_3_2_1_8_1","volume-title":"1706.05098","author":"Ruder S","year":"2017","unstructured":"S Ruder , \" An overview of multi-task learning in deep neural networks,\" ar Xiv preprint ar Xiv : 1706.05098 , 2017 . S Ruder, \"An overview of multi-task learning in deep neural networks,\" arXiv preprint arXiv: 1706.05098, 2017."},{"key":"e_1_3_2_1_9_1","volume-title":"1511.07122","author":"Yu F","year":"2015","unstructured":"F Yu and V Koltun , \"Multi-scale context aggregation by dilated convolutions,\" ar Xiv preprint ar Xiv : 1511.07122 , 2015 . F Yu and V Koltun, \"Multi-scale context aggregation by dilated convolutions,\" arXiv preprint arXiv: 1511.07122, 2015."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"L Chen Y Zhu G Papandreou F Schroff and H Adam \"Encoder-decoder with atrous separable convolution for semantic image segmentation \" in Proceedings of the European conference on computer vision (ECCV) 2018 pp. 801--818.  L Chen Y Zhu G Papandreou F Schroff and H Adam \"Encoder-decoder with atrous separable convolution for semantic image segmentation \" in Proceedings of the European conference on computer vision (ECCV) 2018 pp. 801--818.","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.178"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1986.4767851"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2004.1273918"},{"key":"e_1_3_2_1_14_1","first-page":"4380","article-title":"Deepedge: A multi-scale bifurcated deep network for top-down contour detection","author":"Bertasius G","year":"2015","unstructured":"G Bertasius , J Shi , and L Torresani , \" Deepedge: A multi-scale bifurcated deep network for top-down contour detection ,\" in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015 , pp. 4380 -- 4389 . G Bertasius, J Shi, and L Torresani, \"Deepedge: A multi-scale bifurcated deep network for top-down contour detection,\" in Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 4380--4389.","journal-title":"Proceedings of the IEEE conference on computer vision and pattern recognition"},{"key":"e_1_3_2_1_15_1","first-page":"3982","article-title":"Deepcontour: A deep convolutional feature learned by positive-sharing loss for contour detection","author":"Shen W","year":"2015","unstructured":"W Shen , X Wang , Y Wang , X Bai , and Z Zhang , \" Deepcontour: A deep convolutional feature learned by positive-sharing loss for contour detection ,\" in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015 , pp. 3982 -- 3991 . W Shen, X Wang, Y Wang, X Bai, and Z Zhang, \"Deepcontour: A deep convolutional feature learned by positive-sharing loss for contour detection,\" in Proceedings of the IEEE conference on computer vision and pattern recognition, 2015, pp. 3982--3991.","journal-title":"Proceedings of the IEEE conference on computer vision and pattern recognition"},{"key":"e_1_3_2_1_16_1","first-page":"1395","volume-title":"Proceedings of the IEEE international conference on computer vision, 2015","author":"Xie S","year":"2015","unstructured":"S Xie and Z Tu , \"Holistically-nested edge detection,\" in Proceedings of the IEEE international conference on computer vision, 2015 , pp. 1395 -- 1403 . 10.1109\/ICCV. 2015 .164 S Xie and Z Tu, \"Holistically-nested edge detection,\" in Proceedings of the IEEE international conference on computer vision, 2015, pp. 1395--1403. 10.1109\/ICCV.2015.164"},{"key":"e_1_3_2_1_17_1","first-page":"4545","article-title":"Semantic image segmentation with task-specific edge detection using cnns and a discriminatively trained domain transform","author":"Chen LC","year":"2016","unstructured":"LC Chen , JT Barron , G Papandreou , K Murphy , and AL Yuille , \" Semantic image segmentation with task-specific edge detection using cnns and a discriminatively trained domain transform ,\" in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016 , pp. 4545 -- 4554 . LC Chen, JT Barron, G Papandreou, K Murphy, and AL Yuille, \"Semantic image segmentation with task-specific edge detection using cnns and a discriminatively trained domain transform,\" in Proceedings of the IEEE conference on computer vision and pattern recognition, 2016, pp. 4545--4554.","journal-title":"Proceedings of the IEEE conference on computer vision and pattern recognition"},{"key":"e_1_3_2_1_18_1","first-page":"1855","volume-title":"IEEE","author":"Lyu H","year":"2019","unstructured":"H Lyu , H Fu , X Hu , and L Liu , \"Esnet : Edge-based segmentation network for real-time semantic segmentation in traffic scenes,\" in 2019 IEEE International Conference on Image Processing (ICIP) . IEEE , 2019 , pp. 1855 -- 1859 . H Lyu, H Fu, X Hu, and L Liu, \"Esnet: Edge-based segmentation network for real-time semantic segmentation in traffic scenes,\" in 2019 IEEE International Conference on Image Processing (ICIP). IEEE, 2019, pp. 1855--1859."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.5555\/3045118.3045336"},{"key":"e_1_3_2_1_20_1","first-page":"3156","article-title":"Residual attention network for image classification","author":"Wang F","year":"2017","unstructured":"F Wang , M Jiang , C Qian , S Yang , C Li , H Zhang , X Wang , and X Tang , \" Residual attention network for image classification ,\" in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017 , pp. 3156 -- 3164 . F Wang, M Jiang, C Qian, S Yang, C Li, H Zhang, X Wang, and X Tang, \"Residual attention network for image classification,\" in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 3156--3164.","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"e_1_3_2_1_21_1","first-page":"3640","article-title":"Attention to scale: Scale-aware semantic image segmentation","author":"Chen L","year":"2016","unstructured":"L Chen , Y Yang , J Wang , W Xu , and AL Yuille , \" Attention to scale: Scale-aware semantic image segmentation ,\" in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016 , pp. 3640 -- 3649 . L Chen, Y Yang, J Wang, W Xu, and AL Yuille, \"Attention to scale: Scale-aware semantic image segmentation,\" in Proceedings of the IEEE conference on computer vision and pattern recognition, 2016, pp. 3640--3649.","journal-title":"Proceedings of the IEEE conference on computer vision and pattern recognition"},{"key":"e_1_3_2_1_22_1","first-page":"7794","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Wang X","year":"2018","unstructured":"X Wang , R Girshick , A Gupta , and K He , \"Non-local neural networks,\" in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018 , pp. 7794 -- 7803 . X Wang, R Girshick, A Gupta, and K He, \"Non-local neural networks,\" in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 7794--7803."},{"key":"e_1_3_2_1_23_1","first-page":"3146","article-title":"Dual attention network for scene segmentation","author":"Fu J","year":"2019","unstructured":"J Fu , J Liu , H Tian , Y Li , Y Bao , Z Fang , and H Lu , \" Dual attention network for scene segmentation ,\" in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019 , pp. 3146 -- 3154 . J Fu, J Liu, H Tian, Y Li, Y Bao, Z Fang, and H Lu, \"Dual attention network for scene segmentation,\" in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019, pp. 3146--3154.","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"e_1_3_2_1_24_1","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He K","year":"2016","unstructured":"K He , X Zhang , S Ren , and J Sun , \" Deep residual learning for image recognition ,\" in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016 , pp. 770 -- 778 . K He, X Zhang, S Ren, and J Sun, \"Deep residual learning for image recognition,\" in Proceedings of the IEEE conference on computer vision and pattern recognition, 2016, pp. 770--778.","journal-title":"Proceedings of the IEEE conference on computer vision and pattern recognition"},{"key":"e_1_3_2_1_25_1","first-page":"1925","article-title":"Refmenet: Multipath refinement networks for high-resolution semantic segmentation","author":"Lin G","year":"2017","unstructured":"G Lin , A Milan , C Shen , and I Reid , \" Refmenet: Multipath refinement networks for high-resolution semantic segmentation ,\" in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017 , pp. 1925 -- 1934 . G Lin, A Milan, C Shen, and I Reid, \"Refmenet: Multipath refinement networks for high-resolution semantic segmentation,\" in Proceedings of the IEEE conference on computer vision and pattern recognition, 2017, pp. 1925--1934.","journal-title":"Proceedings of the IEEE conference on computer vision and pattern recognition"},{"key":"e_1_3_2_1_26_1","first-page":"4353","article-title":"Large kernel matters-improve semantic segmentation by global convolutional network","author":"Peng C","year":"2017","unstructured":"C Peng , X Zhang , G Yu , G Luo , and J Sun , \" Large kernel matters-improve semantic segmentation by global convolutional network ,\" in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017 , pp. 4353 -- 4361 . C Peng, X Zhang, G Yu, G Luo, and J Sun, \"Large kernel matters-improve semantic segmentation by global convolutional network,\" in Proceedings of the IEEE conference on computer vision and pattern recognition, 2017, pp. 4353--4361.","journal-title":"Proceedings of the IEEE conference on computer vision and pattern recognition"},{"key":"e_1_3_2_1_27_1","first-page":"1451","volume-title":"IEEE","author":"Wang P","year":"2018","unstructured":"P Wang , P Chen , Y Yuan , D Liu , Z Huang , X Hou , and G Cottrell , \"Understanding convolution for semantic segmentation,\" in 2018 IEEE winter conference on applications of computer vision (WACV) . IEEE , 2018 , pp. 1451 -- 1460 . P Wang, P Chen, Y Yuan, D Liu, Z Huang, X Hou, and G Cottrell, \"Understanding convolution for semantic segmentation,\" in 2018 IEEE winter conference on applications of computer vision (WACV). IEEE, 2018, pp. 1451--1460."},{"key":"e_1_3_2_1_28_1","first-page":"2031","article-title":"Scale adaptive convolutions for scene parsing","author":"Zhang R","year":"2017","unstructured":"R Zhang , S Tang , Y Zhang , J Li , and S Yan , \" Scale adaptive convolutions for scene parsing ,\" in Proceedings of the IEEE International Conference on Computer Vision , 2017 , pp. 2031 -- 2039 . R Zhang, S Tang, Y Zhang, J Li, and S Yan, \"Scale adaptive convolutions for scene parsing,\" in Proceedings of the IEEE International Conference on Computer Vision, 2017, pp. 2031--2039.","journal-title":"Proceedings of the IEEE International Conference on Computer Vision"},{"key":"e_1_3_2_1_29_1","first-page":"2881","article-title":"Pyramid scene parsing network","author":"Zhao H","year":"2017","unstructured":"H Zhao , J Shi , X Qi , X Wang , and J Jia , \" Pyramid scene parsing network ,\" in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017 , pp. 2881 -- 2890 . H Zhao, J Shi, X Qi, X Wang, and J Jia, \"Pyramid scene parsing network,\" in Proceedings of the IEEE conference on computer vision and pattern recognition, 2017, pp. 2881--2890.","journal-title":"Proceedings of the IEEE conference on computer vision and pattern recognition"}],"event":{"name":"ICCAI '20: 2020 6th International Conference on Computing and Artificial Intelligence","sponsor":["University of Tsukuba University of Tsukuba"],"location":"Tianjin China","acronym":"ICCAI '20"},"container-title":["Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3404555.3404624","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3404555.3404624","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:38:59Z","timestamp":1750199939000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3404555.3404624"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,23]]},"references-count":29,"alternative-id":["10.1145\/3404555.3404624","10.1145\/3404555"],"URL":"https:\/\/doi.org\/10.1145\/3404555.3404624","relation":{},"subject":[],"published":{"date-parts":[[2020,4,23]]},"assertion":[{"value":"2020-08-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}