{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:06:11Z","timestamp":1750309571051,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":18,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,5,25]],"date-time":"2025-05-25T00:00:00Z","timestamp":1748131200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"This research is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)","award":["508330921"],"award-info":[{"award-number":["508330921"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,5,26]]},"DOI":"10.1145\/3715669.3726791","type":"proceedings-article","created":{"date-parts":[[2025,5,24]],"date-time":"2025-05-24T06:57:59Z","timestamp":1748069879000},"page":"1-2","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["NERFs for Scanpath Reconstruction and Generation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7128-298X","authenticated-orcid":false,"given":"Wolfgang","family":"Fuhl","sequence":"first","affiliation":[{"name":"Eberhard Karls Universit\u00e4t T\u00fcbingen, Wilhelm Schickard Institut, T\u00fcbingen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,5,25]]},"reference":[{"key":"e_1_3_3_1_2_1","doi-asserted-by":"crossref","unstructured":"Dandan Ding Zhan Ma Di Chen Qingshuang Chen Zoe Liu and Fengqing Zhu. 2021. Advances in video compression system using deep neural network: A review and case studies. Proc. IEEE 109 9 (2021) 1494\u20131520.","DOI":"10.1109\/JPROC.2021.3059994"},{"key":"e_1_3_3_1_3_1","doi-asserted-by":"crossref","unstructured":"Mahmoud Elbattah Colm Loughnane Jean-Luc Gu\u00e9rin Romuald Carette Federica Cilia and Gilles Dequen. 2021. Variational autoencoder for image-based augmentation of eye-tracking data. Journal of Imaging 7 5 (2021) 83.","DOI":"10.3390\/jimaging7050083"},{"key":"e_1_3_3_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3314111.3323074"},{"key":"e_1_3_3_1_5_1","unstructured":"Wolfgang Fuhl and Enkelejda Kasneci. 2018. Eye movement velocity and gaze data generator for evaluation robustness testing and assess of eye tracking software and visualization tools. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1808.09296 (2018)."},{"key":"e_1_3_3_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9413268"},{"key":"e_1_3_3_1_7_1","unstructured":"Kyle Gao Yina Gao Hongjie He Dening Lu Linlin Xu and Jonathan Li. 2022. Nerf: Neural radiance field in 3d vision a comprehensive review. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2210.00379 (2022)."},{"key":"e_1_3_3_1_8_1","unstructured":"Drew\u00a0Thomas Guarnera. 2024. SrcGaze: Automated Fixation Error Correction to Support Eye Tracking Studies on Source Code. Ph.\u00a0D. Dissertation. Kent State University."},{"key":"e_1_3_3_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_3_1_10_1","doi-asserted-by":"crossref","unstructured":"Mohammad Khadir Mohammad\u00a0Farukh Hashmi Deepali\u00a0M Kotambkar and Aditya Gupta. 2024. Innovative Insights: A Review of Deep Learning Methods for Enhanced Video Compression. IEEE Access (2024).","DOI":"10.1109\/ACCESS.2024.3450814"},{"key":"e_1_3_3_1_11_1","doi-asserted-by":"crossref","unstructured":"Siwei Ma Xinfeng Zhang Chuanmin Jia Zhenghui Zhao Shiqi Wang and Shanshe Wang. 2019. Image and video compression with neural networks: A review. IEEE Transactions on Circuits and Systems for Video Technology 30 6 (2019) 1683\u20131698.","DOI":"10.1109\/TCSVT.2019.2910119"},{"key":"e_1_3_3_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/VR.2019.8798107"},{"key":"e_1_3_3_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2578153.2578164"},{"key":"e_1_3_3_1_14_1","doi-asserted-by":"crossref","unstructured":"Ben Mildenhall Pratul\u00a0P Srinivasan Matthew Tancik Jonathan\u00a0T Barron Ravi Ramamoorthi and Ren Ng. 2021. Nerf: Representing scenes as neural radiance fields for view synthesis. Commun. ACM 65 1 (2021) 99\u2013106.","DOI":"10.1145\/3503250"},{"key":"e_1_3_3_1_15_1","first-page":"71","volume-title":"Proceedings of the first workshop on eye-tracking and natural language processing","author":"Mishra Abhijit","year":"2012","unstructured":"Abhijit Mishra, Michael Carl, and Pushpak Bhattacharyya. 2012. A heuristic-based approach for systematic error correction of gaze data for reading. In Proceedings of the first workshop on eye-tracking and natural language processing. 71\u201380."},{"key":"e_1_3_3_1_16_1","doi-asserted-by":"crossref","unstructured":"Frank Rosenblatt. 1958. The perceptron: a probabilistic model for information storage and organization in the brain.Psychological review 65 6 (1958) 386.","DOI":"10.1037\/h0042519"},{"key":"e_1_3_3_1_17_1","unstructured":"A Vaswani. 2017. Attention is all you need. Advances in Neural Information Processing Systems (2017)."},{"key":"e_1_3_3_1_18_1","doi-asserted-by":"crossref","unstructured":"Zeynep Y\u00fccel Albert\u00a0Ali Salah \u00c7etin Meri\u00e7li Tekin Meri\u00e7li Roberto Valenti and Theo Gevers. 2013. Joint attention by gaze interpolation and saliency. IEEE Transactions on cybernetics 43 3 (2013) 829\u2013842.","DOI":"10.1109\/TSMCB.2012.2216979"},{"key":"e_1_3_3_1_19_1","doi-asserted-by":"crossref","unstructured":"Yunzhan Zhou Tian Feng Shihui Shuai Xiangdong Li Lingyun Sun and Henry Been-Lirn Duh. 2022. EDVAM: a 3D eye-tracking dataset for visual attention modeling in a virtual museum. Frontiers of Information Technology & Electronic Engineering 23 1 (2022) 101\u2013112.","DOI":"10.1631\/FITEE.2000318"}],"event":{"name":"ETRA '25: 2025 Symposium on Eye Tracking Research and Applications","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction","SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques"],"location":"Tokyo Japan","acronym":"ETRA '25"},"container-title":["Proceedings of the 2025 Symposium on Eye Tracking Research and Applications"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3715669.3726791","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:19:13Z","timestamp":1750295953000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3715669.3726791"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,25]]},"references-count":18,"alternative-id":["10.1145\/3715669.3726791","10.1145\/3715669"],"URL":"https:\/\/doi.org\/10.1145\/3715669.3726791","relation":{},"subject":[],"published":{"date-parts":[[2025,5,25]]},"assertion":[{"value":"2025-05-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}