{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T09:55:18Z","timestamp":1777888518323,"version":"3.51.4"},"reference-count":67,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T00:00:00Z","timestamp":1760832000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,19]]},"DOI":"10.1109\/iccv51701.2025.00747","type":"proceedings-article","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:45:49Z","timestamp":1777491949000},"page":"7969-7979","source":"Crossref","is-referenced-by-count":0,"title":["Learning Normal Flow Directly from Events"],"prefix":"10.1109","author":[{"given":"Dehao","family":"Yuan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Levi","family":"Burner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiayi","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minghui","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingxi","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiannis","family":"Aloimonos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cornelia","family":"Ferm\u00fcller","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","volume-title":"scipy.stats.circstd","year":"2024"},{"key":"ref2","volume-title":"The aperture problem","year":"2024"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2020.3010468"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2986748"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2014.2347207"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-19258-1_27"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107759"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2011.11.001"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2013.2273537"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3136358"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008132107950"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2015.00137"},{"key":"ref13","article-title":"Evimo2: an event camera dataset for motion segmentation, optical flow, structure from motion, and visual inertial odometry in indoor scenes with monocular or stereo algorithms","author":"Burner","year":"2022","journal-title":"arXiv preprint"},{"key":"ref14","article-title":"Timerewind: Rewinding time with image-and-events video diffusion","author":"Chen","year":"2024","journal-title":"arXiv preprint"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2023.1160034"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793887"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/BF01418980"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00407"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3186770"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/3DV53792.2021.00030"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/3DV53792.2021.00030"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3361671"},{"key":"ref23","first-page":"7167","article-title":"Self-supervised learning of event-based optical flow with spiking neural networks","volume-title":"Advances in Neural Information Processing Systems","author":"Hagenaars","year":"2021"},{"key":"ref24","article-title":"Event-aided time-tocollision estimation for autonomous driving","author":"Li","year":"2024","journal-title":"arXiv preprint"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/IROS55552.2023.10341802"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00888"},{"key":"ref27","article-title":"Adaptive time-slice blockmatching optical flow algorithm for dynamic vision sensors","author":"Liu","year":"2018","journal-title":"BMVC"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3156653"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.15607\/rss.2024.xx.088"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00903"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01816"},{"key":"ref32","article-title":"Rethinking network design and local geometry in point cloud: A simple residual mlp framework","author":"Ma","year":"2022","journal-title":"arXiv preprint"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2015.7139876"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00672"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00889"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1002\/rob.21764"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00901"},{"key":"ref38","first-page":"652","article-title":"Pointnet: Deep learning on point sets for 3d classification and segmentation","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition","author":"Qi","year":"2017"},{"key":"ref39","article-title":"Pointnet++: Deep hierarchical feature learning on point sets in a metric space","volume":"30","author":"Ruizhongtai Qi","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.52202\/068431-1685"},{"key":"ref41","article-title":"Spikepoint: An efficient point-based spiking neural network for event cameras action recognition","author":"Ren","year":"2023","journal-title":"arXiv preprint"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2025.3556561"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72992-8_7"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00401"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2023.3234800"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19797-0_36"},{"key":"ref47","article-title":"Deep complex networks","author":"Trabelsi","year":"2017","journal-title":"arXiv preprint"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3220938"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00920"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3426469"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2019.00199"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2023.3312855"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10610353"},{"key":"ref54","article-title":"Event3dgs: Event-based 3d gaussian splatting for fast egomotion","author":"Xiong","year":"2024","journal-title":"arXiv preprint"},{"key":"ref55","article-title":"Event-based optical flow on neuromorphic processor: Ann vs. snn comparison based on activation sparsification","author":"Xu","year":"2024","journal-title":"arXiv preprint"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00344"},{"key":"ref57","article-title":"Towards anytime optical flow estimation with event cameras","author":"Ye","year":"2023","journal-title":"arXiv preprint"},{"key":"ref58","article-title":"Vector-symbolic architecture for event-based optical flow","author":"You","year":"2024","journal-title":"arXiv preprint"},{"key":"ref59","first-page":"57871","article-title":"A linear time and space local point cloud geometry encoder via vectorized kernel mixture (VecKM)","volume-title":"Proceedings of the 41st International Conference on Machine Learning","author":"Yuan","year":"2024"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2024.109580"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00517"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.3390\/mi14010203"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01595"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.52202\/068431-0574"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2018.2800793"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2018.XIV.062"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00108"}],"event":{"name":"2025 IEEE\/CVF International Conference on Computer Vision (ICCV)","location":"Honolulu, HI, USA","start":{"date-parts":[[2025,10,19]]},"end":{"date-parts":[[2025,10,25]]}},"container-title":["2025 IEEE\/CVF International Conference on Computer Vision (ICCV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11443115\/11443287\/11443615.pdf?arnumber=11443615","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T04:44:52Z","timestamp":1777610692000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11443615\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,19]]},"references-count":67,"URL":"https:\/\/doi.org\/10.1109\/iccv51701.2025.00747","relation":{},"subject":[],"published":{"date-parts":[[2025,10,19]]}}}