{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T10:14:34Z","timestamp":1743070474493,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031064296"},{"type":"electronic","value":"9783031064302"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-06430-2_44","type":"book-chapter","created":{"date-parts":[[2022,5,16]],"date-time":"2022-05-16T08:03:16Z","timestamp":1652688196000},"page":"528-540","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Interactive Deep Annotation as\u00a0DARos: Object Detection Supervision for\u00a0Efficient Instance Segmentation"],"prefix":"10.1007","author":[{"given":"Lihao","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rachid","family":"Benmokhtar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xavier","family":"Perrotton","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,5,17]]},"reference":[{"key":"44_CR1","doi-asserted-by":"crossref","unstructured":"Acuna, D., Ling, H., Kar, A., Fidler, S.: Efficient interactive annotation of segmentation datasets with Polygon-RNN++. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 859\u2013868 (2018)","DOI":"10.1109\/CVPR.2018.00096"},{"key":"44_CR2","doi-asserted-by":"crossref","unstructured":"Bai, J., Wu, X.: Error-tolerant scribbles based interactive image segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 392\u2013399 (2014)","DOI":"10.1109\/CVPR.2014.57"},{"key":"44_CR3","doi-asserted-by":"crossref","unstructured":"Bai, X., Sapiro, G.: A geodesic framework for fast interactive image and video segmentation and matting. In: IEEE 11th International Conference on Computer Vision, pp. 1\u20138 (2007)","DOI":"10.1109\/ICCV.2007.4408931"},{"key":"44_CR4","doi-asserted-by":"crossref","unstructured":"Boykov, Y.Y., Jolly, M.: Interactive graph cuts for optimal boundary region segmentation of objects in N-D images. In: Proceedings Eighth IEEE International Conference on Computer Vision, vol. 1, pp. 105\u2013112 (2001)","DOI":"10.1109\/ICCV.2001.937505"},{"key":"44_CR5","doi-asserted-by":"crossref","unstructured":"Castrej\u00f3n, L., Kundu, K., Urtasun, R., Fidler, S.: Annotating object instances with a Polygon-RNN. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 4485\u20134493 (2017)","DOI":"10.1109\/CVPR.2017.477"},{"key":"44_CR6","doi-asserted-by":"crossref","unstructured":"Cordts, M., et al.: The cityscapes dataset for semantic urban scene understanding. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3213\u20133223 (2016)","DOI":"10.1109\/CVPR.2016.350"},{"issue":"2","key":"44_CR7","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","volume":"88","author":"M Everingham","year":"2010","unstructured":"Everingham, M., Gool, L.V., Williams, C.K.I., Winn, J.M., Zisserman, A.: The pascal visual object classes (VOC) challenge. Int. J. Comput. Vis. 88(2), 303\u2013338 (2010)","journal-title":"Int. J. Comput. Vis."},{"key":"44_CR8","doi-asserted-by":"crossref","unstructured":"Geiger, A., Lenz, P., Urtasun, R.: Are we ready for autonomous driving? The KITTI vision benchmark suite. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3354\u20133361 (2012)","DOI":"10.1109\/CVPR.2012.6248074"},{"issue":"11","key":"44_CR9","doi-asserted-by":"publisher","first-page":"1768","DOI":"10.1109\/TPAMI.2006.233","volume":"28","author":"L Grady","year":"2006","unstructured":"Grady, L.: Random walks for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 28(11), 1768\u20131783 (2006)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"44_CR10","doi-asserted-by":"crossref","unstructured":"Gulshan, V., Rother, C., Criminisi, A., Blake, A., Zisserman, A.: Geodesic star convexity for interactive image segmentation. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 3129\u20133136 (2010)","DOI":"10.1109\/CVPR.2010.5540073"},{"key":"44_CR11","doi-asserted-by":"crossref","unstructured":"Hariharan, B., Arbel\u00e1ez, P., Bourdev, L., Maji, S., Malik, J.: Semantic contours from inverse detectors. In: International Conference on Computer Vision, pp. 991\u2013998 (2011)","DOI":"10.1109\/ICCV.2011.6126343"},{"key":"44_CR12","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"44_CR13","doi-asserted-by":"crossref","unstructured":"Jang, W., Kim, C.: Interactive image segmentation via backpropagating refinement scheme. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 5292\u20135301 (2019)","DOI":"10.1109\/CVPR.2019.00544"},{"key":"44_CR14","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization (2014)"},{"key":"44_CR15","doi-asserted-by":"crossref","unstructured":"Li, Z., Chen, Q., Koltun, V.: Interactive image segmentation with latent diversity. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 577\u2013585 (2018)","DOI":"10.1109\/CVPR.2018.00067"},{"key":"44_CR16","doi-asserted-by":"crossref","unstructured":"Liew, J., Wei, Y., Xiong, W., Ong, S., Feng, J.: Regional interactive image segmentation networks. In: IEEE International Conference on Computer Vision, pp. 2746\u20132754 (2017)","DOI":"10.1109\/ICCV.2017.297"},{"key":"44_CR17","doi-asserted-by":"crossref","unstructured":"Liew, J.H., Cohen, S., Price, B., Mai, L., Feng, J.: Deep interactive thin object selection. In: Winter Conference on Applications of Computer Vision (2021)","DOI":"10.1109\/WACV48630.2021.00035"},{"key":"44_CR18","doi-asserted-by":"crossref","unstructured":"Lin, T., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., Belongie, S.: Feature pyramid networks for object detection. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 936\u2013944 (2017)","DOI":"10.1109\/CVPR.2017.106"},{"key":"44_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"T-Y Lin","year":"2014","unstructured":"Lin, T.-Y., et al.: Microsoft COCO: common objects in context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740\u2013755. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10602-1_48"},{"key":"44_CR20","doi-asserted-by":"crossref","unstructured":"Lin, Z., Zhang, Z., Chen, L.Z., Cheng, M.M., Lu, S.P.: Interactive image segmentation with first click attention. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 13336\u201313345 (2020)","DOI":"10.1109\/CVPR42600.2020.01335"},{"key":"44_CR21","doi-asserted-by":"crossref","unstructured":"Ling, H., Gao, J., Kar, A., Chen, W., Fidler, S.: Fast interactive object annotation with Curve-GCN. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 5252\u20135261 (2019)","DOI":"10.1109\/CVPR.2019.00540"},{"key":"44_CR22","unstructured":"Mahadevan, S., Voigtlaender, P., Leibe, B.: Iteratively trained interactive segmentation. In: British Machine Vision Conference, BMVC, Newcastle, UK, 3\u20136 September 2018, p. 212. BMVA Press (2018)"},{"key":"44_CR23","doi-asserted-by":"crossref","unstructured":"Maninis, K., Caelles, S., Pont-Tuset, J., Van Gool, L.: Deep extreme cut: from extreme points to object segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 616\u2013625 (2018)","DOI":"10.1109\/CVPR.2018.00071"},{"issue":"2","key":"44_CR24","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1016\/j.patcog.2009.03.008","volume":"43","author":"K McGuinness","year":"2010","unstructured":"McGuinness, K., O\u2019Connor, N.E.: A comparative evaluation of interactive segmentation algorithms. Pattern Recognit. 43(2), 434\u2013444 (2010)","journal-title":"Pattern Recognit."},{"key":"44_CR25","doi-asserted-by":"crossref","unstructured":"Papadopoulos, D.P., Uijlings, J.R.R., Keller, F., Ferrari, V.: Extreme clicking for efficient object annotation. In: IEEE International Conference on Computer Vision, pp. 4940\u20134949 (2017)","DOI":"10.1109\/ICCV.2017.528"},{"key":"44_CR26","doi-asserted-by":"crossref","unstructured":"Qin, X., Zhang, Z., Huang, C., Dehghan, M., Zaiane, O.R., Jagersand, M.: U2-net: going deeper with nested u-structure for salient object detection. Pattern Recognit. 106, 107404 (2020)","DOI":"10.1016\/j.patcog.2020.107404"},{"issue":"4","key":"44_CR27","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1007\/s41095-020-0177-5","volume":"6","author":"H Ramadan","year":"2020","unstructured":"Ramadan, H., Lachqar, C., Tairi, H.: A survey of recent interactive image segmentation methods. Comput. Vis. Media 6(4), 355\u2013384 (2020). https:\/\/doi.org\/10.1007\/s41095-020-0177-5","journal-title":"Comput. Vis. Media"},{"issue":"6","key":"44_CR28","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2017","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(6), 1137\u20131149 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"44_CR29","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1145\/1015706.1015720","volume":"23","author":"C Rother","year":"2004","unstructured":"Rother, C., Kolmogorov, V., Blake, A.: GrabCut: interactive foreground extraction using iterated graph cuts. ACM Trans. Graph. 23(3), 309\u2013314 (2004)","journal-title":"ACM Trans. Graph."},{"key":"44_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-019-0197-0","volume":"6","author":"C Shorten","year":"2019","unstructured":"Shorten, C., Khoshgoftaar, T.: A survey on image data augmentation for deep learning. J. Big Data 6, 1\u201348 (2019)","journal-title":"J. Big Data"},{"key":"44_CR31","doi-asserted-by":"crossref","unstructured":"Wang, Z., Acuna, D., Ling, H., Kar, A., Fidler, S.: Object instance annotation with deep extreme level set evolution. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 7492\u20137500 (2019)","DOI":"10.1109\/CVPR.2019.00768"},{"key":"44_CR32","doi-asserted-by":"crossref","unstructured":"Xu, N., Price, B., Cohen, S., Huang, T.: Deep image matting. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 311\u2013320 (2017)","DOI":"10.1109\/CVPR.2017.41"},{"key":"44_CR33","doi-asserted-by":"crossref","unstructured":"Xu, N., Price, B., Cohen, S., Yang, J., Huang, T.: Deep interactive object selection. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 373\u2013381 (2016)","DOI":"10.1109\/CVPR.2016.47"},{"key":"44_CR34","doi-asserted-by":"crossref","unstructured":"Zhang, S., Liew, J.H., Wei, Y., Wei, S., Zhao, Y.: Interactive object segmentation with inside-outside guidance. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 12231\u201312241 (2020)","DOI":"10.1109\/CVPR42600.2020.01225"}],"container-title":["Lecture Notes in Computer Science","Image Analysis and Processing \u2013 ICIAP 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-06430-2_44","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T22:35:06Z","timestamp":1727217306000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-06430-2_44"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031064296","9783031064302"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-06430-2_44","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"17 May 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIAP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image Analysis and Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lecce","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 May 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 May 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iciap2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iciap2021.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Microsoft","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"307","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"168","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"55% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}