{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T16:38:43Z","timestamp":1778258323487,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":44,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T00:00:00Z","timestamp":1665360000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Key Research and Development Program of Hubei Province","award":["2021BAA187"],"award-info":[{"award-number":["2021BAA187"]}]},{"name":"Special Fund of Hubei Luojia Laboratory","award":["220100015"],"award-info":[{"award-number":["220100015"]}]},{"name":"National Natural Science Foundation of China","award":["62176188"],"award-info":[{"award-number":["62176188"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,10]]},"DOI":"10.1145\/3503161.3548766","type":"proceedings-article","created":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T15:42:35Z","timestamp":1665416555000},"page":"7300-7308","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":19,"title":["Learnable Privacy-Preserving Anonymization for Pedestrian Images"],"prefix":"10.1145","author":[{"given":"Junwu","family":"Zhang","sequence":"first","affiliation":[{"name":"Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mang","family":"Ye","sequence":"additional","affiliation":[{"name":"Wuhan University &amp; Hubei Luojia Laboratory, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yao","family":"Yang","sequence":"additional","affiliation":[{"name":"Zhejiang Lab, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,10,10]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"crossref","unstructured":"Jia-Wei Chen Li-Ju Chen Chia-Mu Yu and Chun-Shien Lu. 2021. Perceptual Indistinguishability-Net (PI-Net): Facial Image Obfuscation with Manipulable Semantics. In CVPR. 6478--6487.  Jia-Wei Chen Li-Ju Chen Chia-Mu Yu and Chun-Shien Lu. 2021. Perceptual Indistinguishability-Net (PI-Net): Facial Image Obfuscation with Manipulable Semantics. In CVPR. 6478--6487.","DOI":"10.1109\/CVPR46437.2021.00641"},{"key":"e_1_3_2_2_2_1","unstructured":"Deepfake. 2020. Deepfakes faceswap. https:\/\/github.com\/deepfakes\/faceswap.  Deepfake. 2020. Deepfakes faceswap. https:\/\/github.com\/deepfakes\/faceswap."},{"key":"e_1_3_2_2_3_1","volume-title":"Imagenet: A large-scale hierarchical image database. In CVPR. 248--255.","author":"Deng Jia","year":"2009","unstructured":"Jia Deng , Wei Dong , Richard Socher , Li-Jia Li , Kai Li , and Li Fei-Fei . 2009 . Imagenet: A large-scale hierarchical image database. In CVPR. 248--255. Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009. Imagenet: A large-scale hierarchical image database. In CVPR. 248--255."},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"crossref","unstructured":"Julia Dietlmeier Feiyan Hu Frances Ryan Noel E O'Connor and Kevin McGuinness. 2022. Improving Person Re-Identification with Temporal Constraints. In CVPR. 540--549.  Julia Dietlmeier Feiyan Hu Frances Ryan Noel E O'Connor and Kevin McGuinness. 2022. Improving Person Re-Identification with Temporal Constraints. In CVPR. 540--549.","DOI":"10.1109\/WACVW54805.2022.00060"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"crossref","unstructured":"Cynthia Dwork. 2008. Differential privacy: A survey of results. In TAMC. 1--19.  Cynthia Dwork. 2008. Differential privacy: A survey of results. In TAMC. 1--19.","DOI":"10.1007\/978-3-540-79228-4_1"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"crossref","unstructured":"Cynthia Dwork Frank McSherry Kobbi Nissim and Adam Smith. 2006. Calibrating noise to sensitivity in private data analysis. In TCC. 265--284.  Cynthia Dwork Frank McSherry Kobbi Nissim and Adam Smith. 2006. Calibrating noise to sensitivity in private data analysis. In TCC. 265--284.","DOI":"10.1007\/11681878_14"},{"key":"e_1_3_2_2_7_1","unstructured":"Facebook. 2021. An Update On Our Use of Face Recognition. https:\/\/about.fb.com\/news\/2021\/11\/update-on-use-of-face-recognition.  Facebook. 2021. An Update On Our Use of Face Recognition. https:\/\/about.fb.com\/news\/2021\/11\/update-on-use-of-face-recognition."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"crossref","unstructured":"Oran Gafni Lior Wolf and Yaniv Taigman. 2019. Live face de-identification in video. In ICCV. 9378--9387.  Oran Gafni Lior Wolf and Yaniv Taigman. 2019. Live face de-identification in video. In ICCV. 9378--9387.","DOI":"10.1109\/ICCV.2019.00947"},{"key":"e_1_3_2_2_9_1","unstructured":"Ian J. Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron C. Courville and Yoshua Bengio. 2014. Generative Adversarial Nets. In NIPS.  Ian J. Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron C. Courville and Yoshua Bengio. 2014. Generative Adversarial Nets. In NIPS."},{"key":"e_1_3_2_2_10_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In CVPR. 770--778.  Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In CVPR. 770--778."},{"key":"e_1_3_2_2_11_1","volume-title":"Deepprivacy: A generative adversarial network for face anonymization. In ISVC. 565--578.","author":"Hukkel\u00e5s H\u00e5kon","year":"2019","unstructured":"H\u00e5kon Hukkel\u00e5s , Rudolf Mester , and Frank Lindseth . 2019 . Deepprivacy: A generative adversarial network for face anonymization. In ISVC. 565--578. H\u00e5kon Hukkel\u00e5s, Rudolf Mester, and Frank Lindseth. 2019. Deepprivacy: A generative adversarial network for face anonymization. In ISVC. 565--578."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"crossref","unstructured":"Phillip Isola Jun-Yan Zhu Tinghui Zhou and Alexei A Efros. 2017. Image-to-image translation with conditional adversarial networks. In CVPR. 1125--1134.  Phillip Isola Jun-Yan Zhu Tinghui Zhou and Alexei A Efros. 2017. Image-to-image translation with conditional adversarial networks. In CVPR. 1125--1134.","DOI":"10.1109\/CVPR.2017.632"},{"key":"e_1_3_2_2_13_1","volume-title":"Kallista Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, et al.","author":"Kairouz Peter","year":"2019","unstructured":"Peter Kairouz , H Brendan McMahan , Brendan Avent , Aur\u00e9lien Bellet , Mehdi Bennis , Arjun Nitin Bhagoji , Kallista Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, et al. 2019 . Advances and open problems in federated learning. arXiv preprint arXiv:1912.04977 (2019). Peter Kairouz, H Brendan McMahan, Brendan Avent, Aur\u00e9lien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, et al. 2019. Advances and open problems in federated learning. arXiv preprint arXiv:1912.04977 (2019)."},{"key":"e_1_3_2_2_14_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba . 2014 . Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014). Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.06.061"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"crossref","unstructured":"Zhenzhong Kuang Huigui Liu Jun Yu Aikui Tian Lei Wang Jianping Fan and Noboru Babaguchi. 2021b. Effective De-identification Generative Adversarial Network for Face Anonymization. In ACM MM. 3182--3191.  Zhenzhong Kuang Huigui Liu Jun Yu Aikui Tian Lei Wang Jianping Fan and Noboru Babaguchi. 2021b. Effective De-identification Generative Adversarial Network for Face Anonymization. In ACM MM. 3182--3191.","DOI":"10.1145\/3474085.3475464"},{"key":"e_1_3_2_2_17_1","first-page":"0","article-title":"Anonymousnet: Natural face de-identification with measurable privacy","author":"Li Tao","year":"2019","unstructured":"Tao Li and Lei Lin . 2019 . Anonymousnet: Natural face de-identification with measurable privacy . In CVPR. 0 - 0 . Tao Li and Lei Lin. 2019. Anonymousnet: Natural face de-identification with measurable privacy. In CVPR. 0-0.","journal-title":"CVPR."},{"key":"e_1_3_2_2_18_1","first-page":"2597","article-title":"A strong baseline and batch normalization neck for deep person re-identification","volume":"22","author":"Luo Hao","year":"2019","unstructured":"Hao Luo , Wei Jiang , Youzhi Gu , Fuxu Liu , Xingyu Liao , Shenqi Lai , and Jianyang Gu . 2019 . A strong baseline and batch normalization neck for deep person re-identification . ACM MM , Vol. 22 , 10 (2019), 2597 -- 2609 . Hao Luo, Wei Jiang, Youzhi Gu, Fuxu Liu, Xingyu Liao, Shenqi Lai, and Jianyang Gu. 2019. A strong baseline and batch normalization neck for deep person re-identification. ACM MM, Vol. 22, 10 (2019), 2597--2609.","journal-title":"ACM MM"},{"key":"e_1_3_2_2_19_1","volume-title":"Ciagan: Conditional identity anonymization generative adversarial networks. In CVPR. 5447--5456.","author":"Maximov Maxim","year":"2020","unstructured":"Maxim Maximov , Ismail Elezi , and Laura Leal-Taix\u00e9 . 2020 . Ciagan: Conditional identity anonymization generative adversarial networks. In CVPR. 5447--5456. Maxim Maximov, Ismail Elezi, and Laura Leal-Taix\u00e9. 2020. Ciagan: Conditional identity anonymization generative adversarial networks. In CVPR. 5447--5456."},{"key":"e_1_3_2_2_20_1","unstructured":"Brendan McMahan Eider Moore Daniel Ramage Seth Hampson and Blaise Aguera y Arcas. 2017. Communication-efficient learning of deep networks from decentralized data. In AISTATS. 1273--1282.  Brendan McMahan Eider Moore Daniel Ramage Seth Hampson and Blaise Aguera y Arcas. 2017. Communication-efficient learning of deep networks from decentralized data. In AISTATS. 1273--1282."},{"key":"e_1_3_2_2_21_1","volume-title":"The uu-net: Reversible face de-identification for visual surveillance video footage. arXiv preprint arXiv:2007.04316","author":"Hugo Proencc","year":"2020","unstructured":"Hugo Proencc a. 2020. The uu-net: Reversible face de-identification for visual surveillance video footage. arXiv preprint arXiv:2007.04316 ( 2020 ). Hugo Proencc a. 2020. The uu-net: Reversible face de-identification for visual surveillance video footage. arXiv preprint arXiv:2007.04316 (2020)."},{"key":"e_1_3_2_2_22_1","volume-title":"Yong Jae Lee, and Michael S Ryoo","author":"Ren Zhongzheng","year":"2018","unstructured":"Zhongzheng Ren , Yong Jae Lee, and Michael S Ryoo . 2018 . Learning to anonymize faces for privacy preserving action detection. In ECCV. 620--636. Zhongzheng Ren, Yong Jae Lee, and Michael S Ryoo. 2018. Learning to anonymize faces for privacy preserving action detection. In ECCV. 620--636."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"crossref","unstructured":"Ergys Ristani Francesco Solera Roger Zou Rita Cucchiara and Carlo Tomasi. 2016. Performance measures and a data set for multi-target multi-camera tracking. In ECCV. 17--35.  Ergys Ristani Francesco Solera Roger Zou Rita Cucchiara and Carlo Tomasi. 2016. Performance measures and a data set for multi-target multi-camera tracking. In ECCV. 17--35.","DOI":"10.1007\/978-3-319-48881-3_2"},{"key":"e_1_3_2_2_24_1","volume-title":"Seong Joon Oh","author":"Sun Qianru","year":"2018","unstructured":"Qianru Sun , Liqian Ma , Seong Joon Oh , Luc Van Gool, Bernt Schiele , and Mario Fritz. 2018 a. Natural and effective obfuscation by head inpainting. In CVPR. 5050--5059. Qianru Sun, Liqian Ma, Seong Joon Oh, Luc Van Gool, Bernt Schiele, and Mario Fritz. 2018a. Natural and effective obfuscation by head inpainting. In CVPR. 5050--5059."},{"key":"e_1_3_2_2_25_1","unstructured":"Qianru Sun Ayush Tewari Weipeng Xu Mario Fritz Christian Theobalt and Bernt Schiele. 2018b. A hybrid model for identity obfuscation by face replacement. In ECCV. 553--569.  Qianru Sun Ayush Tewari Weipeng Xu Mario Fritz Christian Theobalt and Bernt Schiele. 2018b. A hybrid model for identity obfuscation by face replacement. In ECCV. 553--569."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.128"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"crossref","unstructured":"Guanshuo Wang Yufeng Yuan Xiong Chen Jiwei Li and Xi Zhou. 2018. Learning discriminative features with multiple granularities for person re-identification. In ACM MM. 274--282.  Guanshuo Wang Yufeng Yuan Xiong Chen Jiwei Li and Xi Zhou. 2018. Learning discriminative features with multiple granularities for person re-identification. In ACM MM. 274--282.","DOI":"10.1145\/3240508.3240552"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"crossref","unstructured":"Xiaogang Wang Gianfranco Doretto Thomas Sebastian Jens Rittscher and Peter Tu. 2007. Shape and appearance context modeling. In ICCV. 1--8.  Xiaogang Wang Gianfranco Doretto Thomas Sebastian Jens Rittscher and Peter Tu. 2007. Shape and appearance context modeling. In ICCV. 1--8.","DOI":"10.1109\/ICCV.2007.4409019"},{"key":"e_1_3_2_2_29_1","first-page":"600","article-title":"Image quality assessment: from error visibility to structural similarity","volume":"13","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 TIP , Vol. 13 , 4 (2004), 600 -- 612 . Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli. 2004. Image quality assessment: from error visibility to structural similarity. IEEE TIP, Vol. 13, 4 (2004), 600--612.","journal-title":"IEEE TIP"},{"key":"e_1_3_2_2_30_1","unstructured":"Longhui Wei Shiliang Zhang Wen Gao and Qi Tian. 2018. Person transfer gan to bridge domain gap for person re-identification. In CVPR. 79--88.  Longhui Wei Shiliang Zhang Wen Gao and Qi Tian. 2018. Person transfer gan to bridge domain gap for person re-identification. In CVPR. 79--88."},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"crossref","unstructured":"Yandong Wen Kaipeng Zhang Zhifeng Li and Yu Qiao. 2016. A discriminative feature learning approach for deep face recognition. In ECCV. 499--515.  Yandong Wen Kaipeng Zhang Zhifeng Li and Yu Qiao. 2016. A discriminative feature learning approach for deep face recognition. In ECCV. 499--515.","DOI":"10.1007\/978-3-319-46478-7_31"},{"key":"e_1_3_2_2_32_1","volume-title":"Privacy-protective-gan for face de-identification. arXiv preprint arXiv:1806.08906","author":"Wu Yifan","year":"2018","unstructured":"Yifan Wu , Fan Yang , and Haibin Ling . 2018. Privacy-protective-gan for face de-identification. arXiv preprint arXiv:1806.08906 ( 2018 ). Yifan Wu, Fan Yang, and Haibin Ling. 2018. Privacy-protective-gan for face de-identification. arXiv preprint arXiv:1806.08906 (2018)."},{"key":"e_1_3_2_2_33_1","volume-title":"A study of face obfuscation in imagenet. arXiv preprint arXiv:2103.06191","author":"Yang Kaiyu","year":"2021","unstructured":"Kaiyu Yang , Jacqueline Yau , Li Fei-Fei , Jia Deng , and Olga Russakovsky . 2021. A study of face obfuscation in imagenet. arXiv preprint arXiv:2103.06191 ( 2021 ). Kaiyu Yang, Jacqueline Yau, Li Fei-Fei, Jia Deng, and Olga Russakovsky. 2021. A study of face obfuscation in imagenet. arXiv preprint arXiv:2103.06191 (2021)."},{"key":"e_1_3_2_2_34_1","first-page":"386","article-title":"Dynamic tri-level relation mining with attentive graph for visible infrared re-identification","volume":"17","author":"Ye Mang","year":"2021","unstructured":"Mang Ye , Cuiqun Chen , Jianbing Shen , and Ling Shao . 2021 a. Dynamic tri-level relation mining with attentive graph for visible infrared re-identification . IEEE TIFS , Vol. 17 (2021), 386 -- 398 . Mang Ye, Cuiqun Chen, Jianbing Shen, and Ling Shao. 2021a. Dynamic tri-level relation mining with attentive graph for visible infrared re-identification. IEEE TIFS, Vol. 17 (2021), 386--398.","journal-title":"IEEE TIFS"},{"key":"e_1_3_2_2_35_1","first-page":"379","article-title":"Collaborative refining for person re-identification with label noise","volume":"31","author":"Ye Mang","year":"2021","unstructured":"Mang Ye , He Li , Bo Du , Jianbing Shen , Ling Shao , and Steven CH Hoi . 2021 b. Collaborative refining for person re-identification with label noise . IEEE TIP , Vol. 31 (2021), 379 -- 391 . Mang Ye, He Li, Bo Du, Jianbing Shen, Ling Shao, and Steven CH Hoi. 2021b. Collaborative refining for person re-identification with label noise. IEEE TIP, Vol. 31 (2021), 379--391.","journal-title":"IEEE TIP"},{"key":"e_1_3_2_2_36_1","volume-title":"Deep learning for person re-identification: A survey and outlook","author":"Ye Mang","year":"2021","unstructured":"Mang Ye , Jianbing Shen , Gaojie Lin , Tao Xiang , Ling Shao , and Steven CH Hoi . 2021c. Deep learning for person re-identification: A survey and outlook . IEEE TPAMI ( 2021 ). Mang Ye, Jianbing Shen, Gaojie Lin, Tao Xiang, Ling Shao, and Steven CH Hoi. 2021c. Deep learning for person re-identification: A survey and outlook. IEEE TPAMI (2021)."},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3013379"},{"key":"e_1_3_2_2_38_1","unstructured":"Zhengxin You Sheng Li Zhenxing Qian and Xinpeng Zhang. 2021. Reversible Privacy-Preserving Recognition. In ICME. 1--6.  Zhengxin You Sheng Li Zhenxing Qian and Xinpeng Zhang. 2021. Reversible Privacy-Preserving Recognition. In ICME. 1--6."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"crossref","unstructured":"Liang Zheng Liyue Shen Lu Tian Shengjin Wang Jingdong Wang and Qi Tian. 2015. Scalable person re-identification: A benchmark. In ICCV. 1116--1124.  Liang Zheng Liyue Shen Lu Tian Shengjin Wang Jingdong Wang and Qi Tian. 2015. Scalable person re-identification: A benchmark. In ICCV. 1116--1124.","DOI":"10.1109\/ICCV.2015.133"},{"key":"e_1_3_2_2_40_1","unstructured":"Kaiyang Zhou Ziwei Liu Yu Qiao Tao Xiang and Chen Change Loy. 2021a. Domain generalization: A survey. (2021).  Kaiyang Zhou Ziwei Liu Yu Qiao Tao Xiang and Chen Change Loy. 2021a. Domain generalization: A survey. (2021)."},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"crossref","unstructured":"Kaiyang Zhou Yongxin Yang Andrea Cavallaro and Tao Xiang. 2019. Omni-scale feature learning for person re-identification. In CVPR. 3702--3712.  Kaiyang Zhou Yongxin Yang Andrea Cavallaro and Tao Xiang. 2019. Omni-scale feature learning for person re-identification. In CVPR. 3702--3712.","DOI":"10.1109\/ICCV.2019.00380"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3069237"},{"key":"e_1_3_2_2_43_1","volume-title":"Domain generalization with mixstyle. arXiv preprint arXiv:2104.02008","author":"Zhou Kaiyang","year":"2021","unstructured":"Kaiyang Zhou , Yongxin Yang , Yu Qiao , and Tao Xiang . 2021c. Domain generalization with mixstyle. arXiv preprint arXiv:2104.02008 ( 2021 ). Kaiyang Zhou, Yongxin Yang, Yu Qiao, and Tao Xiang. 2021c. Domain generalization with mixstyle. arXiv preprint arXiv:2104.02008 (2021)."},{"key":"e_1_3_2_2_44_1","unstructured":"Jun-Yan Zhu Taesung Park Phillip Isola and Alexei A Efros. 2017. Unpaired image-to-image translation using cycle-consistent adversarial networks. In ICCV. 2223--2232.  Jun-Yan Zhu Taesung Park Phillip Isola and Alexei A Efros. 2017. Unpaired image-to-image translation using cycle-consistent adversarial networks. In ICCV. 2223--2232."}],"event":{"name":"MM '22: The 30th ACM International Conference on Multimedia","location":"Lisboa Portugal","acronym":"MM '22","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 30th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3503161.3548766","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3503161.3548766","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:17Z","timestamp":1750182557000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3503161.3548766"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,10]]},"references-count":44,"alternative-id":["10.1145\/3503161.3548766","10.1145\/3503161"],"URL":"https:\/\/doi.org\/10.1145\/3503161.3548766","relation":{},"subject":[],"published":{"date-parts":[[2022,10,10]]},"assertion":[{"value":"2022-10-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}