{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T11:18:46Z","timestamp":1770203926715,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":45,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T00:00:00Z","timestamp":1720569600000},"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":[[2024,7,10]]},"DOI":"10.1145\/3663529.3663832","type":"proceedings-article","created":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T19:43:13Z","timestamp":1720640593000},"page":"104-114","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Neat: Mobile App Layout Similarity Comparison Based on Graph Convolutional Networks"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-3209-9804","authenticated-orcid":false,"given":"Zhu","family":"Tao","sequence":"first","affiliation":[{"name":"ByteDance, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-2984-0770","authenticated-orcid":false,"given":"Yongqiang","family":"Gao","sequence":"additional","affiliation":[{"name":"ByteDance, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7536-0244","authenticated-orcid":false,"given":"Jiayi","family":"Qi","sequence":"additional","affiliation":[{"name":"ByteDance, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2843-0689","authenticated-orcid":false,"given":"Chao","family":"Peng","sequence":"additional","affiliation":[{"name":"ByteDance, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7371-1036","authenticated-orcid":false,"given":"Qinyun","family":"Wu","sequence":"additional","affiliation":[{"name":"ByteDance, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9145-2662","authenticated-orcid":false,"given":"Xiang","family":"Chen","sequence":"additional","affiliation":[{"name":"ByteDance, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9862-6983","authenticated-orcid":false,"given":"Ping","family":"Yang","sequence":"additional","affiliation":[{"name":"Bytedance, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2024,7,10]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2747626"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.572"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3387903.3389308"},{"key":"e_1_3_2_1_4_1","volume-title":"Unsupervised learning of visual features by contrasting cluster assignments. Advances in neural information processing systems, 33","author":"Caron Mathilde","year":"2020","unstructured":"Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin. 2020. Unsupervised learning of visual features by contrasting cluster assignments. Advances in neural information processing systems, 33 (2020), 9912\u20139924."},{"key":"e_1_3_2_1_5_1","volume-title":"Siamese graph convolutional network for content based remote sensing image retrieval. Computer vision and image understanding, 184","author":"Chaudhuri Ushasi","year":"2019","unstructured":"Ushasi Chaudhuri, Biplab Banerjee, and Avik Bhattacharya. 2019. Siamese graph convolutional network for content based remote sensing image retrieval. Computer vision and image understanding, 184 (2019), 22\u201330."},{"key":"e_1_3_2_1_6_1","volume-title":"International conference on machine learning. 1597\u20131607","author":"Chen Ting","year":"2020","unstructured":"Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020. A simple framework for contrastive learning of visual representations. In International conference on machine learning. 1597\u20131607."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01549"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3126594.3126651"},{"key":"e_1_3_2_1_9_1","volume-title":"Yolox: Exceeding yolo series in","author":"Ge Zheng","year":"2021","unstructured":"Zheng Ge, Songtao Liu, Feng Wang, Zeming Li, and Jian Sun. 2021. Yolox: Exceeding yolo series in 2021. arXiv preprint arXiv:2107.08430."},{"key":"e_1_3_2_1_10_1","volume-title":"Zhaohan Guo, and Mohammad Gheshlaghi Azar.","author":"Grill Jean-Bastien","year":"2020","unstructured":"Jean-Bastien Grill, Florian Strub, Florent Altch\u00e9, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, and Mohammad Gheshlaghi Azar. 2020. Bootstrap your own latent-a new approach to self-supervised learning. Advances in neural information processing systems, 33 (2020), 21271\u201321284."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE.2019.00042"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"e_1_3_2_1_13_1","unstructured":"Alexander Hermans Lucas Beyer and Bastian Leibe. 2017. In defense of the triplet loss for person re-identification. arXiv preprint arXiv:1703.07737."},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining. 2735\u20132743","author":"Jia Xiaowei","year":"2020","unstructured":"Xiaowei Jia, Handong Zhao, Zhe Lin, Ajinkya Kale, and Vipin Kumar. 2020. Personalized image retrieval with sparse graph representation learning. In Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining. 2735\u20132743."},{"key":"e_1_3_2_1_15_1","unstructured":"G Jocher. 2022. Ultralytics\/yolov5: v7. 0\u2014YOLOv5 SOTA Realtime Instance Segmentation."},{"key":"e_1_3_2_1_16_1","unstructured":"Gregory Koch Richard Zemel and Ruslan Salakhutdinov. 2015. Siamese neural networks for one-shot image recognition. In ICML deep learning workshop. 2 0."},{"key":"e_1_3_2_1_17_1","volume-title":"2015 IEEE 8th international conference on software testing, verification and validation (ICST). 1\u201310","author":"Lelli Val\u00e9ria","year":"2015","unstructured":"Val\u00e9ria Lelli, Arnaud Blouin, and Benoit Baudry. 2015. Classifying and qualifying GUI defects. In 2015 IEEE 8th international conference on software testing, verification and validation (ICST). 1\u201310."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASE.2019.00104"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"e_1_3_2_1_20_1","volume-title":"Lucas N Kristen, and Claudio Jung.","author":"Llerena Jeffri M","year":"2021","unstructured":"Jeffri M Llerena, Luis Felipe Zeni, Lucas N Kristen, and Claudio Jung. 2021. Gaussian bounding boxes and probabilistic intersection-over-union for object detection. arXiv preprint arXiv:2106.06072."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3551349.3559505"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2491411.2491450"},{"key":"e_1_3_2_1_23_1","volume-title":"2015 IEEE 8th International Conference on Software Testing, Verification and Validation (ICST). 1\u201310","author":"Mahajan Sonal","year":"2015","unstructured":"Sonal Mahajan and William GJ Halfond. 2015. Detection and localization of html presentation failures using computer vision-based techniques. In 2015 IEEE 8th International Conference on Software Testing, Verification and Validation (ICST). 1\u201310."},{"key":"e_1_3_2_1_24_1","volume-title":"2016 IEEE International Conference on Software Testing, Verification and Validation (ICST). 191\u2013201","author":"Mahajan Sonal","year":"2016","unstructured":"Sonal Mahajan, Bailan Li, Pooyan Behnamghader, and William GJ Halfond. 2016. Using visual symptoms for debugging presentation failures in web applications. In 2016 IEEE International Conference on Software Testing, Verification and Validation (ICST). 191\u2013201."},{"key":"e_1_3_2_1_25_1","volume-title":"European Conference on Computer Vision. 730\u2013746","author":"Manandhar Dipu","year":"2020","unstructured":"Dipu Manandhar, Dan Ruta, and John Collomosse. 2020. Learning structural similarity of user interface layouts using graph networks. In European Conference on Computer Vision. 730\u2013746."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSE.2018.2844788"},{"key":"e_1_3_2_1_27_1","volume-title":"2022 IEEE International Conference on Software Maintenance and Evolution (ICSME). 543\u2013552","author":"Peng Chao","year":"2022","unstructured":"Chao Peng, Zhao Zhang, Zhengwei Lv, and Ping Yang. 2022. MUBot: Learning to Test Large-Scale Commercial Android Apps like a Human. In 2022 IEEE International Conference on Software Maintenance and Evolution (ICSME). 543\u2013552."},{"key":"e_1_3_2_1_28_1","volume-title":"Faster r-cnn: Towards real-time object detection with region proposal networks. Advances in neural information processing systems, 28","author":"Ren Shaoqing","year":"2015","unstructured":"Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. 2015. Faster r-cnn: Towards real-time object detection with region proposal networks. Advances in neural information processing systems, 28 (2015)."},{"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":"10.1088\/0031-9155\/45\/8\/315"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460319.3464800"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3468264.3473109"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.683"},{"key":"e_1_3_2_1_34_1","volume-title":"2009 IEEE 12th international conference on computer vision. 32\u201339","author":"Wang Xiaoyu","year":"2009","unstructured":"Xiaoyu Wang, Tony X Han, and Shuicheng Yan. 2009. An HOG-LBP human detector with partial occlusion handling. In 2009 IEEE 12th international conference on computer vision. 32\u201339."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"e_1_3_2_1_36_1","volume-title":"Image quality assessment: from error visibility to structural similarity","author":"Wang Zhou","year":"2004","unstructured":"Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli. 2004. Image quality assessment: from error visibility to structural similarity. IEEE transactions on image processing, 13, 4 (2004), 600\u2013612."},{"key":"e_1_3_2_1_37_1","unstructured":"Wikipedia. 2024. Longest common subsequence. https:\/\/en.wikipedia.org\/wiki\/Longest_common_subsequence"},{"key":"e_1_3_2_1_38_1","unstructured":"Wikipedia. 2024. Mean Average Precision. https:\/\/en.wikipedia.org\/wiki\/Evaluation_measures_(information_retrieval)"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377811.3380416"},{"key":"e_1_3_2_1_40_1","volume-title":"Eighth International Conference on Digital Image Processing (ICDIP","author":"Yuan Zheng-Wu","year":"2016","unstructured":"Zheng-Wu Yuan and Jun Zhang. 2016. Feature extraction and image retrieval based on AlexNet. In Eighth International Conference on Digital Image Processing (ICDIP 2016). 10033, 65\u201369."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICST.2014.31"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40649-019-0069-y"},{"key":"e_1_3_2_1_43_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence. 34","author":"Zhang Zhaolong","year":"2020","unstructured":"Zhaolong Zhang, Yuejie Zhang, Rui Feng, Tao Zhang, and Weiguo Fan. 2020. Zero-shot sketch-based image retrieval via graph convolution network. In Proceedings of the AAAI Conference on Artificial Intelligence. 34, 12943\u201312950."},{"key":"e_1_3_2_1_44_1","volume-title":"Object detection with deep learning: A review","author":"Zhao Zhong-Qiu","year":"2019","unstructured":"Zhong-Qiu Zhao, Peng Zheng, Shou-tao Xu, and Xindong Wu. 2019. Object detection with deep learning: A review. IEEE transactions on neural networks and learning systems, 30, 11 (2019), 3212\u20133232."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.01.001"}],"event":{"name":"FSE '24: 32nd ACM International Conference on the Foundations of Software Engineering","location":"Porto de Galinhas Brazil","acronym":"FSE '24","sponsor":["SIGSOFT ACM Special Interest Group on Software Engineering"]},"container-title":["Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3663529.3663832","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3663529.3663832","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T23:44:21Z","timestamp":1750290261000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3663529.3663832"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,10]]},"references-count":45,"alternative-id":["10.1145\/3663529.3663832","10.1145\/3663529"],"URL":"https:\/\/doi.org\/10.1145\/3663529.3663832","relation":{},"subject":[],"published":{"date-parts":[[2024,7,10]]},"assertion":[{"value":"2024-07-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}