{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T16:39:10Z","timestamp":1782405550564,"version":"3.54.5"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030585419","type":"print"},{"value":"9783030585426","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-58542-6_44","type":"book-chapter","created":{"date-parts":[[2020,11,16]],"date-time":"2020-11-16T17:06:34Z","timestamp":1605546394000},"page":"730-746","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Learning Structural Similarity of User Interface Layouts Using Graph Networks"],"prefix":"10.1007","author":[{"given":"Dipu","family":"Manandhar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Ruta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Collomosse","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,11,17]]},"reference":[{"key":"44_CR1","doi-asserted-by":"crossref","unstructured":"Ashual, O., Wolf, L.: Specifying object attributes and relations in interactive scene generation. In: Proceedings of ICCV (2019)","DOI":"10.1109\/ICCV.2019.00466"},{"key":"44_CR2","doi-asserted-by":"crossref","unstructured":"Beltramelli, T.: pix2code: generating code from a graphical user interface screenshot. arXiV 1705.07962v2 (2017)","DOI":"10.1145\/3220134.3220135"},{"issue":"4","key":"44_CR3","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/MSP.2017.2693418","volume":"34","author":"MM Bronstein","year":"2017","unstructured":"Bronstein, M.M., Bruna, J., LeCun, Y., Szlam, A., Vandergheynst, P.: Geometric deep learning: going beyond euclidean data. IEEE Signal Process. Mag. 34(4), 18\u201342 (2017)","journal-title":"IEEE Signal Process. Mag."},{"key":"44_CR4","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.cviu.2017.06.007","volume":"164","author":"T Bui","year":"2017","unstructured":"Bui, T., Ribeiro, L., Ponti, M., Collomosse, J.: Compact descriptors for sketch-based image retrieval using a triplet loss convolutional neural network. Comput. Vis. Image Understand. (CVIU) 164, 27\u201337 (2017)","journal-title":"Comput. Vis. Image Understand. (CVIU)"},{"key":"44_CR5","doi-asserted-by":"crossref","unstructured":"Bylinskii, Z., et al.: Learning visual importance for graphic designs and data visualizations. In: Proceedings of ACM UIST (2017)","DOI":"10.1145\/3126594.3126653"},{"key":"44_CR6","unstructured":"Chen, J., Ma, T., Xiao, C.: FastGCN: fast learning with graph convolutional networks via importance sampling. In: Proceedings of International Conference on Learning Representations (ICLR) (2018)"},{"key":"44_CR7","doi-asserted-by":"crossref","unstructured":"Deka, B., et al.: Rico: a mobile app dataset for building data-driven design applications. In: Proceedings of the 30th Annual Symposium on User Interface Software and Technology. UIST 2017 (2017)","DOI":"10.1145\/3126594.3126651"},{"key":"44_CR8","doi-asserted-by":"crossref","unstructured":"Geigel, J., Loui, A.: Automatic page layout using genetic algorithms for electronic albuming. In: Proceedings of Electronic Imaging (2001)","DOI":"10.1117\/12.411879"},{"key":"44_CR9","unstructured":"Goldenbert, E.: Automatic layout of variable-content print data. Master\u2019s thesis, School of Cognitive & Computing Sciences, University of Sussex, UK (2000)"},{"key":"44_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1007\/978-3-319-46466-4_15","volume-title":"Computer Vision \u2013 ECCV 2016","author":"A Gordo","year":"2016","unstructured":"Gordo, A., Almaz\u00e1n, J., Revaud, J., Larlus, D.: Deep image retrieval: learning global representations for image search. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9910, pp. 241\u2013257. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46466-4_15"},{"key":"44_CR11","doi-asserted-by":"crossref","unstructured":"Gu, J., Joty, S., Cai, J., Zhao, H., Yang, X., Wang, G.: Unpaired image captioning via scene graph alignments. In: Proceedings of ICCV (2019)","DOI":"10.1109\/ICCV.2019.01042"},{"key":"44_CR12","doi-asserted-by":"crossref","unstructured":"Guo, L., Liu, J., Tang, J., Li, J., Luo, W., Lu, H.: Aligning linguistic words and visual semantic units for image captioning. In: ACM Multimedia (2019)","DOI":"10.1145\/3343031.3350943"},{"key":"44_CR13","doi-asserted-by":"crossref","unstructured":"Guo, M., Chou, E., Huang, D., Song, S., Yeung, S., Fei-Fei, L.: Neural graph matching networks for few shot 3D action recognition. In: Proceedings of ECCV (2018)","DOI":"10.1007\/978-3-030-01246-5_40"},{"key":"44_CR14","doi-asserted-by":"crossref","unstructured":"Harrington, S., Naveda, J., Jones, R., Roetling, P., Thakkar, N.: Aesthetic measures for automated document layout. In: Proceedings of the 2004 ACM Symposium on Document Engineering (2004)","DOI":"10.1145\/1030397.1030419"},{"key":"44_CR15","unstructured":"Huang, C., Loy, C.C., Tang, X.: Local similarity-aware deep feature embedding. In: Advances in Neural Information Processing Systems (2016)"},{"key":"44_CR16","doi-asserted-by":"crossref","unstructured":"Hurst, N., Li, W., Marriott, K.: Review of automatic document formatting. In: Proceedings of the ACM Document Engineerin (2009)","DOI":"10.1145\/1600193.1600217"},{"key":"44_CR17","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.neucom.2019.05.024","volume":"357","author":"N Khan","year":"2019","unstructured":"Khan, N., Chaudhuri, U., Banerjee, B., Chaudhuri, S.: Graph convolutional network for multilabel remote sensing scene recognition. J. Neurocomput. 357, 36\u201346 (2019)","journal-title":"J. Neurocomput."},{"key":"44_CR18","doi-asserted-by":"crossref","unstructured":"Kuen, J., Wang, Z., Wang, G.: Recurrent attentional networks for saliency detection. In: Proceedings of the CVPR (2016)","DOI":"10.1109\/CVPR.2016.399"},{"key":"44_CR19","unstructured":"Li, J., Yang, J., Hertzmann, A., Zhang, J., Xu, T.: LayoutGAN: generating graphic layouts with wireframe discriminators. In: Proceedings of the International Conference on Learning Representations (ICLR) (2019)"},{"key":"44_CR20","doi-asserted-by":"publisher","unstructured":"Liu, T.F., Craft, M., Situ, J., Yumer, E., Mech, R., Kumar, R.: Learning design semantics for mobile apps. In: The 31st Annual ACM Symposium on User Interface Software and Technology, UIST 2018, pp. 569\u2013579. ACM, New York (2018). https:\/\/doi.org\/10.1145\/3242587.3242650","DOI":"10.1145\/3242587.3242650"},{"key":"44_CR21","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: Proceedings of the CVPR (2015)","DOI":"10.1109\/CVPR.2015.7298965"},{"issue":"8","key":"44_CR22","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1109\/TVCG.2014.48","volume":"20","author":"P O\u2019Donovan","year":"2014","unstructured":"O\u2019Donovan, P., Agarwala, A., Hertzmann, A.: Learning layouts for single-page graphic designs. IEEE Trans. Visual. Comput. Graph. 20(8), 1200\u20131213 (2014)","journal-title":"IEEE Trans. Visual. Comput. Graph."},{"key":"44_CR23","doi-asserted-by":"crossref","unstructured":"O\u2019Donovan, P., Agarwala, A., Hertzmann, A.: Designscape: design with interactive layout suggestions. In: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pp. 1221\u20131224 (2015)","DOI":"10.1145\/2702123.2702149"},{"key":"44_CR24","doi-asserted-by":"crossref","unstructured":"Oh Song, H., Xiang, Y., Jegelka, S., Savarese, S.: Deep metric learning via lifted structured feature embedding. In: Proceedings of the CVPR (2016)","DOI":"10.1109\/CVPR.2016.434"},{"key":"44_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-319-46448-0_1","volume-title":"Computer Vision \u2013 ECCV 2016","author":"F Radenovi\u0107","year":"2016","unstructured":"Radenovi\u0107, F., Tolias, G., Chum, O.: CNN image retrieval learns from BoW: unsupervised fine-tuning with hard examples. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 3\u201320. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_1"},{"key":"44_CR26","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. In: Proceedings of the NIPS (2015)"},{"key":"44_CR27","doi-asserted-by":"crossref","unstructured":"Sangkloy, P., Burnell, N., Ham, C., Hays, J.: The sketchy database: learning to retrieve badly drawn bunnies. In: Proceedings of the ACM SIGGRAPH (2016)","DOI":"10.1145\/2897824.2925954"},{"key":"44_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1007\/978-3-319-93417-4_38","volume-title":"The Semantic Web","author":"M Schlichtkrull","year":"2018","unstructured":"Schlichtkrull, M., Kipf, T.N., Bloem, P., van\u00a0den Berg, R., Titov, I., Welling, M.: Modeling relational data with graph convolutional networks. In: Gangemi, A., et al. (eds.) ESWC 2018. LNCS, vol. 10843, pp. 593\u2013607. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-93417-4_38"},{"key":"44_CR29","doi-asserted-by":"crossref","unstructured":"Schroff, F., Kalenichenko, D., Philbin, J.: Facenet: a unified embedding for face recognition and clustering. In: Proceedings of the CVPR (2015)","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"44_CR30","unstructured":"Swearngin, A., Dontcheva, M., Li, W., Brandt, J., Dixon, M., Ko, A.: Rewire: interface design assistance from examples. In: Proceedings of the ACM CHI (2018)"},{"key":"44_CR31","doi-asserted-by":"crossref","unstructured":"Tripathi, S., Sridhar, S., Sundaresan, S., Tang, H.: Compact scene graphs for layout composition and patch retrieval. In: Proceedings of the CVPR (2019)","DOI":"10.1109\/CVPRW.2019.00094"},{"key":"44_CR32","doi-asserted-by":"crossref","unstructured":"Wang, J., et al.: Learning fine-grained image similarity with deep ranking. In: Proceedings of the CVPR, pp. 1386\u20131393 (2014)","DOI":"10.1109\/CVPR.2014.180"},{"key":"44_CR33","doi-asserted-by":"crossref","unstructured":"Wang, R., Yan, J., Yang, X.: Learning combinatorial embedding networks for deep graph matching. In: Proceedings of the ICCV (2019)","DOI":"10.1109\/ICCV.2019.00315"},{"key":"44_CR34","doi-asserted-by":"crossref","unstructured":"X. Pang, Y. Cao, R.L., Chan, A.: Directing user attention via visual flow on web designs. In: Proceedings of the ACM SIGGRAPH (2016)","DOI":"10.1145\/2980179.2982422"},{"key":"44_CR35","doi-asserted-by":"crossref","unstructured":"Yang, X., Yumer, E., Asente, P., Kraley, M., Kifer, D., Giles, C.: Learning to extract semantic structure from documents using multimodal fully convolutional neural networks. In: Proceedings of the CVPR, pp. 5315\u20135324 (2017)","DOI":"10.1109\/CVPR.2017.462"},{"key":"44_CR36","unstructured":"Zhang, Z., Cui, P., Zhu, W.: Deep learning on graphs: a survey. arXiV 1812.04202v2 (2019)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-58542-6_44","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,16]],"date-time":"2024-11-16T00:14:10Z","timestamp":1731716050000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-58542-6_44"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030585419","9783030585426"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-58542-6_44","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"17 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Glasgow","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2020.eu\/","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":"OpenReview","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5025","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":"1360","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":"27% - 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":"7","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)"}},{"value":"The conference was held virtually due to the COVID-19 pandemic. From the ECCV Workshops 249 full papers, 18 short papers, and 21 further contributions were published out of a total of 467 submissions.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}