{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T00:29:21Z","timestamp":1766449761973,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030682378"},{"type":"electronic","value":"9783030682385"}],"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.springer.com\/tdm"},{"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.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-68238-5_33","type":"book-chapter","created":{"date-parts":[[2021,1,30]],"date-time":"2021-01-30T07:02:43Z","timestamp":1611990163000},"page":"449-461","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Revisiting the Threat Space for Vision-Based Keystroke Inference Attacks"],"prefix":"10.1007","author":[{"given":"John","family":"Lim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"True","family":"Price","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabian","family":"Monrose","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan-Michael","family":"Frahm","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,31]]},"reference":[{"key":"33_CR1","doi-asserted-by":"crossref","unstructured":"Backes, M., D\u00fcrmuth, M., Unruh, D.: Compromising reflections-or-how to read LCD monitors around the corner. In: 2008 IEEE Symposium on Security and Privacy, SP 2008, pp. 158\u2013169. IEEE (2008)","DOI":"10.1109\/SP.2008.25"},{"key":"33_CR2","doi-asserted-by":"crossref","unstructured":"Backes, M., Chen, T., Duermuth, M., Lensch, H.P.A., Welk, M.: Tempest in a teapot: compromising reflections revisited. In: 2009 30th IEEE Symposium on Security and Privacy, pp. 315\u2013327. IEEE (2009)","DOI":"10.1109\/SP.2009.20"},{"key":"33_CR3","doi-asserted-by":"crossref","unstructured":"Balzarotti, D., Cova, M., Vigna, G.: ClearShot: eavesdropping on keyboard input from video. In: 2008 IEEE Symposium on Security and Privacy, SP 2008, pp. 170\u2013183. IEEE (2008)","DOI":"10.1109\/SP.2008.28"},{"key":"33_CR4","doi-asserted-by":"crossref","unstructured":"Bousmalis, K., Silberman, N., Dohan, D., Erhan, D., Krishnan, D.: Unsupervised pixel-level domain adaptation with generative adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3722\u20133731 (2017)","DOI":"10.1109\/CVPR.2017.18"},{"key":"33_CR5","doi-asserted-by":"crossref","unstructured":"Chen, Y., Li, T., Zhang, R., Zhang, Y., Hedgpeth, T.: EyeTell: video-assisted touchscreen keystroke inference from eye movements. In: 2018 IEEE Symposium on Security and Privacy (SP), pp. 144\u2013160. IEEE (2018)","DOI":"10.1109\/SP.2018.00010"},{"key":"33_CR6","doi-asserted-by":"crossref","unstructured":"Chen, Y., Li, W., Chen, X., Van Gool, L.: Learning semantic segmentation from synthetic data: a geometrically guided input-output adaptation approach. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1841\u20131850 (2019)","DOI":"10.1109\/CVPR.2019.00194"},{"key":"33_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1007\/978-3-319-49409-8_34","volume-title":"Computer Vision \u2013 ECCV 2016 Workshops","author":"B Chu","year":"2016","unstructured":"Chu, B., Madhavan, V., Beijbom, O., Hoffman, J., Darrell, T.: Best practices for fine-tuning visual classifiers to new domains. In: Hua, G., J\u00e9gou, H. (eds.) ECCV 2016. LNCS, vol. 9915, pp. 435\u2013442. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-49409-8_34"},{"key":"33_CR8","doi-asserted-by":"crossref","unstructured":"Cordts, M., et al.: The cityscapes dataset for semantic urban scene understanding. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016)","DOI":"10.1109\/CVPR.2016.350"},{"key":"33_CR9","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., Fei-Fei, L.: ImageNet: a large-scale hierarchical image database (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"33_CR10","doi-asserted-by":"crossref","unstructured":"Dosovitskiy, A., et al.: FlowNet: learning optical flow with convolutional networks. In: IEEE International Conference on Computer Vision (ICCV) (2015). http:\/\/lmb.informatik.uni-freiburg.de\/Publications\/2015\/DFIB15","DOI":"10.1109\/ICCV.2015.316"},{"key":"33_CR11","unstructured":"Hoffman, J., et al.: CyCADA: cycle-consistent adversarial domain adaptation (2018). https:\/\/openreview.net\/forum?id=SktLlGbRZ"},{"key":"33_CR12","unstructured":"Kuhn, M.G.: Compromising emanations: eavesdropping risks of computer displays. Ph.D. thesis, University of Cambridge (2002)"},{"key":"33_CR13","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":"33_CR14","doi-asserted-by":"crossref","unstructured":"Oquab, M., Bottou, L., Laptev, I., Sivic, J.: Learning and transferring mid-level image representations using convolutional neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1717\u20131724 (2014)","DOI":"10.1109\/CVPR.2014.222"},{"key":"33_CR15","doi-asserted-by":"crossref","unstructured":"Peng, X., Usman, B., Saito, K., Kaushik, N., Hoffman, J., Saenko, K.: Syn2Real: a new benchmark for synthetic-to-real visual domain adaptation. arXiv preprint arXiv:1806.09755 (2018)","DOI":"10.1109\/CVPRW.2018.00271"},{"key":"33_CR16","doi-asserted-by":"crossref","unstructured":"Raguram, R., White, A.M., Goswami, D., Monrose, F.Frahm, J.-M.: iSpy: automatic reconstruction of typed input from compromising reflections. In: Proceedings of the 18th ACM Conference on Computer and Communications Security, pp. 527\u2013536. ACM (2011)","DOI":"10.1145\/2046707.2046769"},{"key":"33_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1007\/978-3-319-46475-6_7","volume-title":"Computer Vision \u2013 ECCV 2016","author":"SR Richter","year":"2016","unstructured":"Richter, S.R., Vineet, V., Roth, S., Koltun, V.: Playing for data: ground truth from computer games. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9906, pp. 102\u2013118. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46475-6_7"},{"key":"33_CR18","doi-asserted-by":"crossref","unstructured":"Ros, G., Sellart, L., Materzynska, J., Vazquez, D., Lopez, A.M.: The SYNTHIA dataset: a large collection of synthetic images for semantic segmentation of urban scenes. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3234\u20133243 (2016)","DOI":"10.1109\/CVPR.2016.352"},{"key":"33_CR19","doi-asserted-by":"crossref","unstructured":"Shrivastava, A., Pfister, T., Tuzel, O., Susskind, J., Wang, W., Webb, R.: Learning from simulated and unsupervised images through adversarial training. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2107\u20132116 (2017)","DOI":"10.1109\/CVPR.2017.241"},{"key":"33_CR20","doi-asserted-by":"crossref","unstructured":"Shukla, D., Kumar, R., Serwadda, A., Phoha, V.V.: Beware, your hands reveal your secrets! In: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, pp. 904\u2013917. ACM (2014)","DOI":"10.1145\/2660267.2660360"},{"key":"33_CR21","doi-asserted-by":"crossref","unstructured":"Sun, J., Jin, X., Chen, Y., Zhang, J., Zhang, Y., Zhang, R.: Visible: video-assisted keystroke inference from tablet backside motion. In: NDSS (2016)","DOI":"10.14722\/ndss.2016.23060"},{"key":"33_CR22","doi-asserted-by":"crossref","unstructured":"Tzeng, E., Hoffman, J., Saenko, K., Darrell, T.: Adversarial discriminative domain adaptation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7167\u20137176 (2017)","DOI":"10.1109\/CVPR.2017.316"},{"key":"33_CR23","doi-asserted-by":"crossref","unstructured":"Wood, E., Baltru\u0161aitis, T., Morency, L.-P., Robinson, P., Bulling, A.: Learning an appearance-based gaze estimator from one million synthesised images. In: Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications, pp. 131\u2013138. ACM (2016)","DOI":"10.1145\/2857491.2857492"},{"key":"33_CR24","doi-asserted-by":"crossref","unstructured":"Xu, Y., Heinly, J., White, A.M., Monrose, F., Frahm, J.-M.: Seeing double: reconstructing obscured typed input from repeated compromising reflections. In: Proceedings of the 2013 ACM SIGSAC Conference on Computer & Communications Security, pp. 1063\u20131074. ACM (2013)","DOI":"10.1145\/2508859.2516709"},{"key":"33_CR25","doi-asserted-by":"crossref","unstructured":"Ye, G., et al.: Cracking android pattern lock in five attempts (2017)","DOI":"10.14722\/ndss.2017.23130"},{"key":"33_CR26","doi-asserted-by":"crossref","unstructured":"Yue, Q., Ling, Z., Fu, X., Liu, B., Ren, K., Zhao, W.: Blind recognition of touched keys on mobile devices. In: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, pp. 1403\u20131414. ACM (2014)","DOI":"10.1145\/2660267.2660288"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2020 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-68238-5_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,29]],"date-time":"2025-01-29T23:05:15Z","timestamp":1738191915000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-68238-5_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030682378","9783030682385"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-68238-5_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"31 January 2021","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)"}}]}}