{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:04:59Z","timestamp":1774627499094,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":54,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,6,2]],"date-time":"2020-06-02T00:00:00Z","timestamp":1591056000000},"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":[[2020,6,2]]},"DOI":"10.1145\/3379155.3391317","type":"proceedings-article","created":{"date-parts":[[2020,5,6]],"date-time":"2020-05-06T00:31:32Z","timestamp":1588725092000},"page":"1-10","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["Dataset for Eye Tracking on a Virtual Reality Platform"],"prefix":"10.1145","author":[{"given":"Stephan Joachim","family":"Garbin","sequence":"first","affiliation":[{"name":"University College London"}]},{"given":"Oleg","family":"Komogortsev","sequence":"additional","affiliation":[{"name":"Michigan State University"}]},{"given":"Robert","family":"Cavin","sequence":"additional","affiliation":[{"name":"Facebook"}]},{"given":"Gregory","family":"Hughes","sequence":"additional","affiliation":[{"name":"Facebook Reality Labs"}]},{"given":"Yiru","family":"Shen","sequence":"additional","affiliation":[{"name":"Facebook Reality Labs"}]},{"given":"Immo","family":"Schuetz","sequence":"additional","affiliation":[{"name":"Facebook Reality Labs"}]},{"given":"Sachin S","family":"Talathi","sequence":"additional","affiliation":[{"name":"Facebook, USA"}]}],"member":"320","published-online":{"date-parts":[[2020,6,2]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"1885","article-title":"Iris Segmentation: a survey","volume":"3","author":"Adegoke B.O.","year":"2013","unstructured":"B.O. Adegoke , E.O. Omidiora , S.A. Falohun , and J.A. Ojo . 2013 . Iris Segmentation: a survey . International Journal of Modern Engineering Research (IJMER) 3 , 4(2013), 1885 \u2013 1889 . B.O. Adegoke, E.O. Omidiora, S.A. Falohun, and J.A. Ojo. 2013. Iris Segmentation: a survey. International Journal of Modern Engineering Research (IJMER) 3, 4(2013), 1885\u20131889.","journal-title":"International Journal of Modern Engineering Research (IJMER)"},{"key":"e_1_3_2_1_2_1","volume-title":"Segnet: A deep convolutional encoder-decoder architecture for image segmentation","author":"Badrinarayanan V.","year":"2017","unstructured":"V. Badrinarayanan , A. Kendall , and R. Cipolla . 2017 . Segnet: A deep convolutional encoder-decoder architecture for image segmentation . IEEE transactions on pattern analysis and machine intelligence 39, 12(2017), 2481\u20132495. V. Badrinarayanan, A. Kendall, and R. Cipolla. 2017. Segnet: A deep convolutional encoder-decoder architecture for image segmentation. IEEE transactions on pattern analysis and machine intelligence 39, 12(2017), 2481\u20132495."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"A. Borji and L. Itti. 2013. State-of-the-art in visual attention modeling. IEEE transactions on pattern analysis and machine intelligence 35 1(2013) 185\u2013207.  A. Borji and L. Itti. 2013. State-of-the-art in visual attention modeling. IEEE transactions on pattern analysis and machine intelligence 35 1(2013) 185\u2013207.","DOI":"10.1109\/TPAMI.2012.89"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACPR.2013.168"},{"key":"e_1_3_2_1_5_1","volume-title":"SSERBC 2017: Sclera segmentation and eye recognition benchmarking competition. In 2017 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 742\u2013747","author":"Das A.","unstructured":"A. Das , U. Pal , M.A. Ferrer , M. Blumenstein , D. \u0160tepec , P. Rot , Z. Emer\u0161i\u010d , P. Peer , V. \u0160truc , and S.V. Kumar . 2017 . SSERBC 2017: Sclera segmentation and eye recognition benchmarking competition. In 2017 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 742\u2013747 . A. Das, U. Pal, M.A. Ferrer, M.Blumenstein, D. \u0160tepec, P. Rot, Z. Emer\u0161i\u010d, P. Peer, V. \u0160truc, and S.V. Kumar. 2017. SSERBC 2017: Sclera segmentation and eye recognition benchmarking competition. In 2017 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 742\u2013747."},{"key":"e_1_3_2_1_6_1","volume-title":"SSERBC 2017: Sclera segmentation and eye recognition benchmarking competition. In 2017 IEEE International Joint Conference on Biometrics (IJCB). 742\u2013747","author":"Das A.","year":"2017","unstructured":"A. Das , U. Pal , M.\u00a0 A. Ferrer , M. Blumenstein , D. \u0160tepec , P. Rot , Z. Emersic , P. Peer , V. \u0160truc , S.\u00a0V.\u00a0 A. Kumar , and B.\u00a0 S. Harish . 2017 . SSERBC 2017: Sclera segmentation and eye recognition benchmarking competition. In 2017 IEEE International Joint Conference on Biometrics (IJCB). 742\u2013747 . https:\/\/doi.org\/10.1109\/BTAS.2017.8272764 A. Das, U. Pal, M.\u00a0A. Ferrer, M. Blumenstein, D. \u0160tepec, P. Rot, Z. Emersic, P. Peer, V. \u0160truc, S.\u00a0V.\u00a0A. Kumar, and B.\u00a0S. Harish. 2017. SSERBC 2017: Sclera segmentation and eye recognition benchmarking competition. In 2017 IEEE International Joint Conference on Biometrics (IJCB). 742\u2013747. https:\/\/doi.org\/10.1109\/BTAS.2017.8272764"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"e_1_3_2_1_8_1","volume-title":"Excuse: Robust pupil detection in real-world scenarios. In International Conference on Computer Analysis of Images and Patterns","author":"Fuhl W.","year":"2015","unstructured":"W. Fuhl , T. K\u00fcbler , K. Sippel , W. Rosenstiel , and E. Kasneci . 2015 . Excuse: Robust pupil detection in real-world scenarios. In International Conference on Computer Analysis of Images and Patterns . Springer , 39\u201351. W. Fuhl, T. K\u00fcbler, K. Sippel, W. Rosenstiel, and E. Kasneci. 2015. Excuse: Robust pupil detection in real-world scenarios. In International Conference on Computer Analysis of Images and Patterns. Springer, 39\u201351."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"W. Fuhl W. Rosenstiel and E. Kasneci. 2019. 500 000 Images Closer to Eyelid and Pupil Segmentation. 336\u2013347. https:\/\/doi.org\/10.1007\/978-3-030-29888-3_27  W. Fuhl W. Rosenstiel and E. Kasneci. 2019. 500 000 Images Closer to Eyelid and Pupil Segmentation. 336\u2013347. https:\/\/doi.org\/10.1007\/978-3-030-29888-3_27","DOI":"10.1007\/978-3-030-29888-3_27"},{"key":"e_1_3_2_1_10_1","unstructured":"W. Fuhl T. Santini G. Kasneci and E. Kasneci. 2016a. PupilNet: Convolutional Neural Networks for Robust Pupil Detection. CoRR abs\/1601.04902(2016). arxiv:1601.04902http:\/\/arxiv.org\/abs\/1601.04902  W. Fuhl T. Santini G. Kasneci and E. Kasneci. 2016a. PupilNet: Convolutional Neural Networks for Robust Pupil Detection. CoRR abs\/1601.04902(2016). arxiv:1601.04902http:\/\/arxiv.org\/abs\/1601.04902"},{"key":"e_1_3_2_1_11_1","volume-title":"Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications","author":"Fuhl W.","unstructured":"W. Fuhl , T. Santini , T. K\u00fcbler , and E. Kasneci . 2016b. ElSe: Ellipse Selection for Robust Pupil Detection in Real-world Environments . In Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications ( Charleston, South Carolina) (ETRA \u201916). ACM, New York, NY, USA, 123\u2013130. https:\/\/doi.org\/10.1145\/2857491.2857505 W. Fuhl, T. Santini, T. K\u00fcbler, and E. Kasneci. 2016b. ElSe: Ellipse Selection for Robust Pupil Detection in Real-world Environments. In Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications(Charleston, South Carolina) (ETRA \u201916). ACM, New York, NY, USA, 123\u2013130. https:\/\/doi.org\/10.1145\/2857491.2857505"},{"key":"e_1_3_2_1_12_1","volume-title":"Proceedings of the Symposium on Eye Tracking Research and Applications. ACM, 255\u2013258","author":"Funes M.","unstructured":"M. Funes , A. Kenneth , F. Monay , and J. Odobez . 2014. Eyediap: A database for the development and evaluation of gaze estimation algorithms from rgb and rgb-d cameras . In Proceedings of the Symposium on Eye Tracking Research and Applications. ACM, 255\u2013258 . M. Funes, A. Kenneth, F. Monay, and J. Odobez. 2014. Eyediap: A database for the development and evaluation of gaze estimation algorithms from rgb and rgb-d cameras. In Proceedings of the Symposium on Eye Tracking Research and Applications. ACM, 255\u2013258."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"e_1_3_2_1_14_1","volume-title":"2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 3354\u20133361","author":"Geiger A.","unstructured":"A. Geiger , P. Lenz , and R. Urtasun . 2012. Are we ready for autonomous driving? the kitti vision benchmark suite . In 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 3354\u20133361 . A. Geiger, P. Lenz, and R. Urtasun. 2012. Are we ready for autonomous driving? the kitti vision benchmark suite. In 2012 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 3354\u20133361."},{"key":"e_1_3_2_1_15_1","unstructured":"K. He X. Zhang S. Ren and J. Sun. 2015. Deep Residual Learning for Image Recognition. CoRR abs\/1512.03385(2015). arxiv:1512.03385http:\/\/arxiv.org\/abs\/1512.03385  K. He X. Zhang S. Ren and J. Sun. 2015. Deep Residual Learning for Image Recognition. CoRR abs\/1512.03385(2015). arxiv:1512.03385http:\/\/arxiv.org\/abs\/1512.03385"},{"key":"e_1_3_2_1_16_1","volume-title":"van\u00a0de Weijer","author":"Holmqvist K.","year":"2011","unstructured":"K. Holmqvist , M. Nystr\u00f6m , R. Andersson , R. Dewhurst , H. Jarodzka , and J. van\u00a0de Weijer . 2011 . Eye Tracking : A Comprehensive Guide To Methods And Measures . (01 2011). K. Holmqvist, M. Nystr\u00f6m, R. Andersson, R. Dewhurst, H. Jarodzka, and J. van\u00a0de Weijer. 2011. Eye Tracking: A Comprehensive Guide To Methods And Measures. (01 2011)."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/42.845178"},{"key":"e_1_3_2_1_18_1","volume-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861(2017).","author":"Howard A.G.","year":"2017","unstructured":"A.G. Howard , M. Zhu , B. Chen , D. Kalenichenko , W. Wang , T. Weyand , M. Andreetto , and H. Adam . 2017 . Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861(2017). A.G. Howard, M. Zhu, B. Chen, D. Kalenichenko, W. Wang, T. Weyand, M. Andreetto, and H. Adam. 2017. Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861(2017)."},{"key":"e_1_3_2_1_19_1","unstructured":"Q. Huang A.Veeraraghavan and A. Sabharwal. 2015. TabletGaze: A Dataset and Baseline Algorithms for Unconstrained Appearance-based Gaze Estimation in Mobile Tablets. CoRR abs\/1508.01244(2015). arxiv:1508.01244http:\/\/arxiv.org\/abs\/1508.01244  Q. Huang A.Veeraraghavan and A. Sabharwal. 2015. TabletGaze: A Dataset and Baseline Algorithms for Unconstrained Appearance-based Gaze Estimation in Mobile Tablets. CoRR abs\/1508.01244(2015). arxiv:1508.01244http:\/\/arxiv.org\/abs\/1508.01244"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2009.66"},{"key":"e_1_3_2_1_21_1","unstructured":"J. Johnson M. Douze and H. J\u00e9gou. 2017. Billion-scale similarity search with GPUs. CoRR abs\/1702.08734(2017). arxiv:1702.08734http:\/\/arxiv.org\/abs\/1702.08734  J. Johnson M. Douze and H. J\u00e9gou. 2017. Billion-scale similarity search with GPUs. CoRR abs\/1702.08734(2017). arxiv:1702.08734http:\/\/arxiv.org\/abs\/1702.08734"},{"key":"e_1_3_2_1_22_1","volume-title":"Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Glasgow, Scotland UK) (CHI \u201919)","author":"Kim J.","unstructured":"J. Kim , M. Stengel , A. Majercik , S.\u00a0 De Mello , D. Dunn , S. Laine , M. McGuire , and D. Luebke . 2019. NVGaze: An Anatomically-Informed Dataset for Low-Latency, Near-Eye Gaze Estimation . In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Glasgow, Scotland UK) (CHI \u201919) . ACM, New York, NY, USA, 10. https:\/\/doi.org\/10.1145\/3290605.3300780 J. Kim, M. Stengel, A. Majercik, S.\u00a0De Mello, D. Dunn, S. Laine, M. McGuire, and D. Luebke. 2019. NVGaze: An Anatomically-Informed Dataset for Low-Latency, Near-Eye Gaze Estimation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Glasgow, Scotland UK) (CHI \u201919). ACM, New York, NY, USA, 10. https:\/\/doi.org\/10.1145\/3290605.3300780"},{"key":"e_1_3_2_1_23_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980(2014).","author":"Kingma P.","year":"2014","unstructured":"D.\u00a0 P. Kingma and J. Ba . 2014 . Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980(2014). D.\u00a0P. Kingma and J. Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980(2014)."},{"key":"e_1_3_2_1_24_1","volume-title":"Eye Tracking for Everyone. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Krafka K.","unstructured":"K. Krafka , A. Khosla , P. Kellnhofer , H. Kannan , S. Bhandarkar , W. Matusik , and A. Torralba . 2016 . Eye Tracking for Everyone. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR). K. Krafka, A. Khosla, P. Kellnhofer, H. Kannan, S. Bhandarkar, W. Matusik, and A. Torralba. 2016. Eye Tracking for Everyone. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2015.2473855"},{"key":"e_1_3_2_1_26_1","unstructured":"A. Krizhevsky I. Sutskever and G.E. Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems. 1097\u20131105.  A. Krizhevsky I. Sutskever and G.E. Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in neural information processing systems. 1097\u20131105."},{"key":"e_1_3_2_1_27_1","unstructured":"S. Liang Y. Li and R. Srikant. 2017. Principled Detection of Out-of-Distribution Examples in Neural Networks. CoRR abs\/1706.02690(2017). arxiv:1706.02690http:\/\/arxiv.org\/abs\/1706.02690  S. Liang Y. Li and R. Srikant. 2017. Principled Detection of Out-of-Distribution Examples in Neural Networks. CoRR abs\/1706.02690(2017). arxiv:1706.02690http:\/\/arxiv.org\/abs\/1706.02690"},{"key":"e_1_3_2_1_28_1","unstructured":"T.\u00a0Y. Lin M. Maire S.\u00a0J. Belongie L.\u00a0D. Bourdev R.\u00a0B. Girshick J. Hays P. Perona D. Ramanan P. Doll\u00e1r and C.\u00a0L. Zitnick. 2014. Microsoft COCO: Common Objects in Context. CoRR abs\/1405.0312(2014). arxiv:1405.0312http:\/\/arxiv.org\/abs\/1405.0312  T.\u00a0Y. Lin M. Maire S.\u00a0J. Belongie L.\u00a0D. Bourdev R.\u00a0B. Girshick J. Hays P. Perona D. Ramanan P. Doll\u00e1r and C.\u00a0L. Zitnick. 2014. Microsoft COCO: Common Objects in Context. CoRR abs\/1405.0312(2014). arxiv:1405.0312http:\/\/arxiv.org\/abs\/1405.0312"},{"key":"e_1_3_2_1_29_1","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition. 3431\u20133440","author":"Long J.","unstructured":"J. Long , E. Shelhamer , and T. Darrell . 2015. Fully convolutional networks for semantic segmentation . In Proceedings of the IEEE conference on computer vision and pattern recognition. 3431\u20133440 . J. Long, E. Shelhamer, and T. Darrell. 2015. Fully convolutional networks for semantic segmentation. In Proceedings of the IEEE conference on computer vision and pattern recognition. 3431\u20133440."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"crossref","unstructured":"D.R. Lucio R. Laroca E. Severo A.\u00a0Britto Jr and D. Menotti. 2018. Fully convolutional networks and generative adversarial networks applied to sclera segmentation. CoRR vol. abs\/1806.08722(2018).  D.R. Lucio R. Laroca E. Severo A.\u00a0Britto Jr and D. Menotti. 2018. Fully convolutional networks and generative adversarial networks applied to sclera segmentation. CoRR vol. abs\/1806.08722(2018).","DOI":"10.1109\/BTAS.2018.8698597"},{"key":"e_1_3_2_1_31_1","volume-title":"2018 Imperial College Computing Student Workshop (ICCSW 2018)","author":"Luo B.","year":"2018","unstructured":"B. Luo , J. Shen , Y. Wang , and M. Pantic . 2019. The iBUG Eye Segmentation Dataset . In 2018 Imperial College Computing Student Workshop (ICCSW 2018) (OpenAccess Series in Informatics (OASIcs)), Edoardo Pirovano and Eva Graversen (Eds.), Vol.\u00a066. Schloss Dagstuhl\u2013Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 7:1\u20137:9. https:\/\/doi.org\/10.4230\/OASIcs.ICCSW. 2018 .7 B. Luo, J. Shen, Y. Wang, and M. Pantic. 2019. The iBUG Eye Segmentation Dataset. In 2018 Imperial College Computing Student Workshop (ICCSW 2018)(OpenAccess Series in Informatics (OASIcs)), Edoardo Pirovano and Eva Graversen (Eds.), Vol.\u00a066. Schloss Dagstuhl\u2013Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 7:1\u20137:9. https:\/\/doi.org\/10.4230\/OASIcs.ICCSW.2018.7"},{"key":"e_1_3_2_1_32_1","volume-title":"Proceedings of the Symposium on Eye Tracking Research and Applications","author":"McMurrough D.","unstructured":"C.\u00a0 D. McMurrough , V. Metsis , J. Rich , and F. Makedon . 2012. An Eye Tracking Dataset for Point of Gaze Detection . In Proceedings of the Symposium on Eye Tracking Research and Applications ( Santa Barbara, California) (ETRA \u201912). ACM, New York, NY, USA, 305\u2013308. https:\/\/doi.org\/10.1145\/2168556.2168622 C.\u00a0D. McMurrough, V. Metsis, J. Rich, and F. Makedon. 2012. An Eye Tracking Dataset for Point of Gaze Detection. In Proceedings of the Symposium on Eye Tracking Research and Applications (Santa Barbara, California) (ETRA \u201912). ACM, New York, NY, USA, 305\u2013308. https:\/\/doi.org\/10.1145\/2168556.2168622"},{"key":"e_1_3_2_1_33_1","unstructured":"A. Paszke S. Gross S. Chintala G. Chanan E. Yang Z. DeVito Z. Lin A. Desmaison L. Antiga and A. Lerer. 2017. Automatic differentiation in PyTorch. (2017).  A. Paszke S. Gross S. Chintala G. Chanan E. Yang Z. DeVito Z. Lin A. Desmaison L. Antiga and A. Lerer. 2017. Automatic differentiation in PyTorch. (2017)."},{"key":"e_1_3_2_1_34_1","volume-title":"Perceptually-based Foveated Virtual Reality. In ACM SIGGRAPH 2016 Emerging Technologies","author":"Patney A.","unstructured":"A. Patney , J. Kim , M. Salvi , A. Kaplanyan , C. Wyman , N. Benty , A. Lefohn , and D. Luebke . 2016 . Perceptually-based Foveated Virtual Reality. In ACM SIGGRAPH 2016 Emerging Technologies ( Anaheim, California) (SIGGRAPH \u201916). ACM, New York, NY, USA, Article 17, 2\u00a0pages. https:\/\/doi.org\/10.1145\/2929464.2929472 A. Patney, J. Kim, M. Salvi, A. Kaplanyan, C. Wyman, N. Benty, A. Lefohn, and D. Luebke. 2016. Perceptually-based Foveated Virtual Reality. In ACM SIGGRAPH 2016 Emerging Technologies (Anaheim, California) (SIGGRAPH \u201916). ACM, New York, NY, USA, Article 17, 2\u00a0pages. https:\/\/doi.org\/10.1145\/2929464.2929472"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.189"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2009.66"},{"key":"e_1_3_2_1_37_1","volume-title":"2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS). IEEE, 1\u20136.","author":"Radu P.","unstructured":"P. Radu , J. Ferryman , and P. Wild . 2015. A robust sclera segmentation algorithm . In 2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS). IEEE, 1\u20136. P. Radu, J. Ferryman, and P. Wild. 2015. A robust sclera segmentation algorithm. In 2015 IEEE 7th International Conference on Biometrics Theory, Applications and Systems (BTAS). IEEE, 1\u20136."},{"key":"e_1_3_2_1_38_1","volume-title":"2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI). IEEE, 1\u20138.","author":"Rot P.","unstructured":"P. Rot , Z. Emer\u0161i\u010d , V. Struc , and P. Peer . 2018. Deep multi-class eye segmentation for ocular biometrics . In 2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI). IEEE, 1\u20138. P. Rot, Z. Emer\u0161i\u010d, V. Struc, and P. Peer. 2018. Deep multi-class eye segmentation for ocular biometrics. In 2018 IEEE International Work Conference on Bioinspired Intelligence (IWOBI). IEEE, 1\u20138."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"crossref","unstructured":"W. Sankowski K. Grabowski M. Napieralska M. Zubert and A. Napieralski. 2010. Reliable algorithm for iris segmentation in eye image. Image and vision computing 28 2 (2010) 231\u2013237.  W. Sankowski K. Grabowski M. Napieralska M. Zubert and A. Napieralski. 2010. Reliable algorithm for iris segmentation in eye image. Image and vision computing 28 2 (2010) 231\u2013237.","DOI":"10.1016\/j.imavis.2009.05.014"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2018.02.002"},{"key":"e_1_3_2_1_41_1","unstructured":"A. Shafaei M. Schmidt and J.\u00a0J. Little. 2018. Does Your Model Know the Digit 6 Is Not a Cat? A Less Biased Evaluation of \u201dOutlier\u201d Detectors. CoRR abs\/1809.04729(2018). arxiv:1809.04729http:\/\/arxiv.org\/abs\/1809.04729  A. Shafaei M. Schmidt and J.\u00a0J. Little. 2018. Does Your Model Know the Digit 6 Is Not a Cat? A Less Biased Evaluation of \u201dOutlier\u201d Detectors. CoRR abs\/1809.04729(2018). arxiv:1809.04729http:\/\/arxiv.org\/abs\/1809.04729"},{"key":"e_1_3_2_1_42_1","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition. 2107\u20132116","author":"Shrivastava A.","unstructured":"A. Shrivastava , T. Pfister , O. Tuzel , J. Susskind , W. Wang , and R. Webb . 2017. Learning from simulated and unsupervised images through adversarial training . In Proceedings of the IEEE conference on computer vision and pattern recognition. 2107\u20132116 . A. Shrivastava, T. Pfister, O. Tuzel, J. Susskind, W. Wang, and R. Webb. 2017. Learning from simulated and unsupervised images through adversarial training. In Proceedings of the IEEE conference on computer vision and pattern recognition. 2107\u20132116."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"crossref","unstructured":"B.\u00a0A. Smith Q. Yin S.\u00a0K. Feiner and S.\u00a0K. Nayar. 2013. Gaze locking: passive eye contact detection for human-object interaction. In UIST.  B.\u00a0A. Smith Q. Yin S.\u00a0K. Feiner and S.\u00a0K. Nayar. 2013. Gaze locking: passive eye contact detection for human-object interaction. In UIST.","DOI":"10.1145\/2501988.2501994"},{"key":"e_1_3_2_1_44_1","first-page":"1517","article-title":"Hilbert space embeddings and metrics on probability measures","author":"Sriperumbudur B.K.","year":"2010","unstructured":"B.K. Sriperumbudur , A. Gretton , Kenji K.F., B. Sch\u00f6lkopf , and G. Lanckriet . 2010 . Hilbert space embeddings and metrics on probability measures . Journal of Machine Learning Research 11 , Apr (2010), 1517 \u2013 1561 . B.K. Sriperumbudur, A. Gretton, Kenji K.F., B. Sch\u00f6lkopf, and G. Lanckriet. 2010. Hilbert space embeddings and metrics on probability measures. Journal of Machine Learning Research 11, Apr (2010), 1517\u20131561.","journal-title":"Journal of Machine Learning Research 11"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/2168556.2168585"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/332040.332443"},{"key":"e_1_3_2_1_47_1","unstructured":"Martin Thoma. 2016. A survey of semantic segmentation. arXiv preprint arXiv:1602.06541(2016).  Martin Thoma. 2016. A survey of semantic segmentation. arXiv preprint arXiv:1602.06541(2016)."},{"key":"e_1_3_2_1_48_1","unstructured":"M. Tonsen X. Zhang Y. Sugano and A. Bulling. 2015. Labeled pupils in the wild: A dataset for studying pupil detection in unconstrained environments. CoRR abs\/1511.05768(2015). arxiv:1511.05768http:\/\/arxiv.org\/abs\/1511.05768  M. Tonsen X. Zhang Y. Sugano and A. Bulling. 2015. Labeled pupils in the wild: A dataset for studying pupil detection in unconstrained environments. CoRR abs\/1511.05768(2015). arxiv:1511.05768http:\/\/arxiv.org\/abs\/1511.05768"},{"key":"e_1_3_2_1_49_1","volume-title":"Proceedings Ninth IEEE International Conference on Computer Vision. IEEE, 136\u2013143","author":"Venkateswarlu R.","year":"2003","unstructured":"R. Venkateswarlu . 2003 . Eye gaze estimation from a single image of one eye . In Proceedings Ninth IEEE International Conference on Computer Vision. IEEE, 136\u2013143 . R. Venkateswarlu. 2003. Eye gaze estimation from a single image of one eye. In Proceedings Ninth IEEE International Conference on Computer Vision. IEEE, 136\u2013143."},{"key":"e_1_3_2_1_51_1","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 440\u2013448","author":"Wang K.","unstructured":"K. Wang , R. Zhao , and Q. Ji . 2018. A hierarchical generative model for eye image synthesis and eye gaze estimation . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 440\u2013448 . K. Wang, R. Zhao, and Q. Ji. 2018. A hierarchical generative model for eye image synthesis and eye gaze estimation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 440\u2013448."},{"key":"e_1_3_2_1_52_1","volume-title":"Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications. ACM, 131\u2013138","author":"Wood E.","unstructured":"E. Wood , T. Baltru\u0161aitis , LP. Morency , P. Robinson , and A. Bulling . 2016. Learning an appearance-based gaze estimator from one million synthesised images . In Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications. ACM, 131\u2013138 . E. Wood, T. Baltru\u0161aitis, LP. Morency, P. Robinson, and A. Bulling. 2016. Learning an appearance-based gaze estimator from one million synthesised images. In Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications. ACM, 131\u2013138."},{"key":"e_1_3_2_1_53_1","volume-title":"Proceedings of the IEEE International Conference on Computer Vision. 3756\u20133764","author":"Wood E.","unstructured":"E. Wood , T. Baltrusaitis , X. Zhang , Y. Sugano , P. Robinson , and A. Bulling . 2015. Rendering of eyes for eye-shape registration and gaze estimation . In Proceedings of the IEEE International Conference on Computer Vision. 3756\u20133764 . E. Wood, T. Baltrusaitis, X. Zhang, Y. Sugano, P. Robinson, and A. Bulling. 2015. Rendering of eyes for eye-shape registration and gaze estimation. In Proceedings of the IEEE International Conference on Computer Vision. 3756\u20133764."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3272127.3275032"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299081"}],"event":{"name":"ETRA '20: 2020 Symposium on Eye Tracking Research and Applications","location":"Stuttgart Germany","acronym":"ETRA '20","sponsor":["SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques","SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["ACM Symposium on Eye Tracking Research and Applications"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3379155.3391317","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3379155.3391317","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:44:48Z","timestamp":1750203888000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3379155.3391317"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,2]]},"references-count":54,"alternative-id":["10.1145\/3379155.3391317","10.1145\/3379155"],"URL":"https:\/\/doi.org\/10.1145\/3379155.3391317","relation":{},"subject":[],"published":{"date-parts":[[2020,6,2]]},"assertion":[{"value":"2020-06-02","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}