{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T16:29:16Z","timestamp":1783096156091,"version":"3.54.6"},"reference-count":273,"publisher":"Association for Computing Machinery (ACM)","issue":"8","funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62371269"],"award-info":[{"award-number":["62371269"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Guangdong Innovative and Entrepreneurial Research Team Program","award":["2021ZT09L197"],"award-info":[{"award-number":["2021ZT09L197"]}]},{"name":"Shenzhen Low-Altitude Airspace Strategic Program Portfolio","award":["Z253061"],"award-info":[{"award-number":["Z253061"]}]},{"name":"Meituan Academy of Robotics Shenzhen"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Comput. Surv."],"published-print":{"date-parts":[[2026,6,30]]},"abstract":"<jats:p>\n                    With the evolution of mobile embodied intelligence, agents such as drones and autonomous robots are transitioning toward high agility. This shift imposes stringent demands on embodied perception, requiring high-accuracy and low-latency feedback loops for reliable interaction. Event-based vision has emerged as a transformative paradigm. Its microsecond-level temporal resolution and high dynamic range render it ideal for embodied perception tasks on high-agility mobile platforms. However, asynchronous nature, substantial noise, lack of persistent semantic information, and large data volume pose challenges for processing on resource-constrained mobile agents. This article surveys the literature from 2014\u20132025 and presents a comprehensive overview of event-based mobile embodied perception. We organize review around four key pillars: event\n                    <jats:italic toggle=\"yes\">abstraction<\/jats:italic>\n                    methods, perception\n                    <jats:italic toggle=\"yes\">algorithm<\/jats:italic>\n                    advancements, hardware and software\n                    <jats:italic toggle=\"yes\">acceleration<\/jats:italic>\n                    strategies, and mobile\n                    <jats:italic toggle=\"yes\">applications<\/jats:italic>\n                    . We discuss critical tasks including visual odometry, object tracking, optical flow, and 3D reconstruction, while highlighting challenges associated with sensor fusion and real-time deployment. Furthermore, we outline future research directions, such as improving event cameras with advanced optics and leveraging neuromorphic computing for efficient processing. To support ongoing research, we provide an open-source\n                    <jats:italic toggle=\"yes\">Online Sheet<\/jats:italic>\n                    with recent developments. We hope this survey serves as a reference, facilitating adoption of event-based vision across diverse mobile embodied applications.\n                  <\/jats:p>","DOI":"10.1145\/3786332","type":"journal-article","created":{"date-parts":[[2025,12,25]],"date-time":"2025-12-25T12:07:58Z","timestamp":1766664478000},"page":"1-41","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Event Camera Meets Mobile Embodied Perception: Abstraction, Algorithm, Acceleration, Application"],"prefix":"10.1145","volume":"58","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1392-0362","authenticated-orcid":false,"given":"Haoyang","family":"Wang","sequence":"first","affiliation":[{"name":"Shenzhen International Graduate School, Tsinghua University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8503-1077","authenticated-orcid":false,"given":"Ruishan","family":"Guo","sequence":"additional","affiliation":[{"name":"Shenzhen International Graduate School, Tsinghua University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4801-6470","authenticated-orcid":false,"given":"Pengtao","family":"Ma","sequence":"additional","affiliation":[{"name":"Shenzhen International Graduate School, Tsinghua University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5848-5054","authenticated-orcid":false,"given":"Ciyu","family":"Ruan","sequence":"additional","affiliation":[{"name":"Shenzhen International School, Tsinghua University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8212-321X","authenticated-orcid":false,"given":"Xinyu","family":"Luo","sequence":"additional","affiliation":[{"name":"Shenzhen International Graduate School, Tsinghua University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4103-5558","authenticated-orcid":false,"given":"Wenhua","family":"Ding","sequence":"additional","affiliation":[{"name":"Shenzhen International Graduate School, Tsinghua University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8097-8664","authenticated-orcid":false,"given":"Tianyang","family":"Zhong","sequence":"additional","affiliation":[{"name":"Shenzhen International Graduate School, Tsinghua University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8347-2657","authenticated-orcid":false,"given":"Jingao","family":"Xu","sequence":"additional","affiliation":[{"name":"The University of Hong Kong","place":["Hong Kong, Hong Kong"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8052-9200","authenticated-orcid":false,"given":"Yunhao","family":"Liu","sequence":"additional","affiliation":[{"name":"Tsinghua University","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8271-5023","authenticated-orcid":false,"given":"Xinlei","family":"Chen","sequence":"additional","affiliation":[{"name":"Shenzhen International Graduate School, Tsinghua University","place":["Shenzhen, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,2,4]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"crossref","unstructured":"Xuecheng Chen Haoyang Wang Yuhan Cheng Haohao Fu Yuxuan Liu Fan Dang Yunhao Liu Jinqiang Cui and Xinlei Chen. 2024. DDL: Empowering delivery drones with large-scale urban sensing capability. IEEE Journal of Selected Topics in Signal Processing 18 3 (2024) 502\u2013515.","DOI":"10.1109\/JSTSP.2024.3427371"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.abm5954"},{"key":"e_1_3_2_4_2","doi-asserted-by":"crossref","unstructured":"Zhuozhu Jian Zejia Liu Haoyu Shao Xueqian Wang Xinlei Chen and Bin Liang. 2023. Path generation for wheeled robots autonomous navigation on vegetated terrain. IEEE Robotics and Automation Letters 9 2 (2023) 1764\u20131771.","DOI":"10.1109\/LRA.2023.3334142"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.ado6187"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/3715014.3722048"},{"key":"e_1_3_2_7_2","doi-asserted-by":"crossref","unstructured":"Haoyang Wang Jingao Xu Chenyu Zhao Zihong Lu Yuhan Cheng Xuecheng Chen Xiao-Ping Zhang Yunhao Liu and Xinlei Chen. 2024. Transformloc: Transforming MAVs into mobile localization infrastructures in heterogeneous swarms. In IEEE INFOCOM 2024-IEEE Conference on Computer Communications. IEEE 1101\u20131110.","DOI":"10.1109\/INFOCOM52122.2024.10621375"},{"key":"e_1_3_2_8_2","first-page":"977","volume-title":"Proceedings of the19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22)","author":"Xu Jingao","year":"2022","unstructured":"Jingao Xu, Hao Cao, Zheng Yang, Longfei Shangguan, Jialin Zhang, Xiaowu He, and Yunhao Liu. 2022. \\(\\lbrace\\) SwarmMap \\(\\rbrace\\) : Scaling up real-time collaborative visual \\(\\lbrace\\) SLAM \\(\\rbrace\\) at the edge. In Proceedings of the19th USENIX Symposium on Networked Systems Design and Implementation (NSDI 22). 977\u2013993."},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1145\/3643832.3661872"},{"key":"e_1_3_2_10_2","doi-asserted-by":"crossref","unstructured":"Xuecheng Chen Zijian Xiao Yuhan Cheng Chen-Chun Hsia Haoyang Wang Jingao Xu Susu Xu Fan Dang Xiao-Ping Zhang Yunhao Liu et\u00a0al. 2024. Soscheduler: Toward proactive and adaptive wildfire suppression via multi-UAV collaborative scheduling. IEEE Internet of Things Journal 11 14 (2024) 24858\u201324871.","DOI":"10.1109\/JIOT.2024.3389771"},{"key":"e_1_3_2_11_2","doi-asserted-by":"crossref","unstructured":"Jiaxu Leng Yongming Ye Mengjingcheng Mo Chenqiang Gao Ji Gan Bin Xiao and Xinbo Gao. 2024. Recent advances for aerial object detection: A survey. ACM Computing Surveys 56 12 (2024) 1\u201336.","DOI":"10.1145\/3664598"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/3636534.3694730"},{"key":"e_1_3_2_13_2","article-title":"Aerial shepherds: Enabling hierarchical localization in heterogeneous MAV swarms","author":"Wang Haoyang","year":"2025","unstructured":"Haoyang Wang, Jingao Xu, Chenyu Zhao, Yuhan Cheng, Xuecheng Chen, Chaopeng Hong, Xiao-Ping Zhang, Yunhao Liu, and Xinlei Chen. 2025. Aerial shepherds: Enabling hierarchical localization in heterogeneous MAV swarms. IEEE Transactions on Mobile Computing (2025).","journal-title":"IEEE Transactions on Mobile Computing"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.ade4538"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/3560905.3568432"},{"key":"e_1_3_2_16_2","volume-title":"Proceedings of the 30th ACM MobiCom","author":"Cui Jiahe","year":"2024","unstructured":"Jiahe Cui, Yuze He, Jianwei Niu, Zhenchao Ouyang, and Guoliang Xing. 2024. \\(\\alpha\\) LiDAR: An adaptive high-resolution panoramic LiDAR system. In Proceedings of the 30th ACM MobiCom."},{"key":"e_1_3_2_17_2","unstructured":"Chenyu Zhao Jingao Xu Ciyu Ruan Haoyang Wang Shengbo Wang Jiaqi Li Jirong Zha Weijie Hong Zheng Yang Yunhao Liu et\u00a0al. 2025. Flight dynamics to sensing modalities: Exploiting drone ground effect for accurate edge detection. arXiv:2509.21085. Retrieved from https:\/\/arxiv.org\/abs\/2509.21085"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/3560905.3568519"},{"key":"e_1_3_2_19_2","unstructured":"Haoyang Wang Xinyu Luo Wenhua Ding Jingao Xu Xuecheng Chen Ruiyang Duan Jialong Chen Haitao Zhang Yunhao Liu and Xinlei Chen. 2025. Enabling high-frequency cross-modality visual positioning service for accurate drone landing. arXiv:2510.00646. Retrieved from https:\/\/arxiv.org\/abs\/2510.00646"},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1002\/rob.22109"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1038\/nature14542"},{"key":"e_1_3_2_22_2","unstructured":"DJI MAVIC 4. 2025. Retrieved from https:\/\/enterprise.dji.com\/matrice-4-series?site=enterprise&from=nav"},{"key":"e_1_3_2_23_2","unstructured":"Wing\u2019s drone. 2025. Retrieved from https:\/\/wing.com\/technology"},{"key":"e_1_3_2_24_2","doi-asserted-by":"crossref","unstructured":"Fangcheng Zhu Yunfan Ren Longji Yin Fanze Kong Qingbo Liu Ruize Xue Wenyi Liu Yixi Cai Guozheng Lu Haotian Li and Fu Zhang. 2025. Swarm-LIO2: Decentralized efficient lidar-inertial odometry for aerial swarm systems. IEEE Transactions on Robotics 41 (2025) 960\u2013981.","DOI":"10.1109\/TRO.2024.3522155"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1145\/3643832.3661871"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS54860.2022.00058"},{"key":"e_1_3_2_27_2","unstructured":"Hao Cao Jingao Xu Danyang Li Longfei Shangguan Yunhao Liu and Zheng Yang. 2022. Edge assisted mobile semantic visual SLAM. IEEE Transactions on Mobile Computing 22 12 (2022) 6985\u20136999."},{"key":"e_1_3_2_28_2","unstructured":"Tong Qin Jie Pan Shaozu Cao Shaojie Shen. 2019. A General Optimization-based Framework for Local Odometry Estimation with Multiple Sensors. arXiv:1901.03638. Retrieved from https:\/\/arxiv.org\/abs\/1901.03638"},{"key":"e_1_3_2_29_2","doi-asserted-by":"publisher","unstructured":"Danyang Li Yishujie Zhao Jingao Xu Shengkai Zhang Longfei Shangguan Qiang Ma Xuan Ding and Zheng Yang. 2024. Reshaping edge-assisted visual SLAM by embracing on-chip intelligence. IEEE Transactions on Mobile Computing 23 12 (2024) 12983\u201312997. DOI:10.1109\/TMC.2024.3424452","DOI":"10.1109\/TMC.2024.3424452"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-024-07409-w"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3008413"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2963386"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aaz9712"},{"key":"e_1_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.adj8124"},{"key":"e_1_3_2_35_2","doi-asserted-by":"crossref","unstructured":"Yunhao Zou Ying Fu Tsuyoshi Takatani and Yinqiang Zheng. 2025. EventHDR: From event to high-speed HDR videos and beyond. IEEE Transactions on Pattern Analysis and Machine Intelligence 47 1 (2025) 32\u201350.","DOI":"10.1109\/TPAMI.2024.3469571"},{"key":"e_1_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093366"},{"key":"e_1_3_2_37_2","unstructured":"Xu Zheng Yexin Liu Yunfan Lu Tongyan Hua Tianbo Pan Weiming Zhang Dacheng Tao and Lin Wang. 2023. Deep learning for event-based vision: A comprehensive survey and benchmarks. arXiv:2302.08890. Retrieved from https:\/\/arxiv.org\/abs\/2302.08890. (2023)."},{"key":"e_1_3_2_38_2","unstructured":"Bharatesh Chakravarthi Aayush Atul Verma Kostas Daniilidis Cornelia Fermuller and Yezhou Yang. 2024. Recent event camera innovations: A survey. arXiv:2408.13627. Retrieved from https:\/\/arxiv.org\/abs\/2408.13627. (2024)."},{"key":"e_1_3_2_39_2","doi-asserted-by":"publisher","DOI":"10.1145\/3656469"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3386032"},{"key":"e_1_3_2_41_2","unstructured":"G.Gallego Recent papers on Event-based Vision. 2025. Retrieved from https:\/\/docs.google.com\/spreadsheets\/d\/1_OBbSz10CkxXNDHQd-Mn_ui3OmymMFvm-lW316uvxy8\/edit?pli=1&gid=0#gid=0"},{"key":"e_1_3_2_42_2","doi-asserted-by":"publisher","DOI":"10.1145\/3570361.3613269"},{"key":"e_1_3_2_43_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2007.914337"},{"key":"e_1_3_2_44_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2010.2085952"},{"key":"e_1_3_2_45_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2014.2342715"},{"key":"e_1_3_2_46_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2019.00214"},{"key":"e_1_3_2_47_2","unstructured":"CelePixel CeleX5-MIPI-Stereo SDK GitHub Repository. 2025. Retrieved from https:\/\/github.com\/CelePixel\/CeleX5-MIPI-Stereo"},{"key":"e_1_3_2_48_2","unstructured":"Prophesee GenX320 Metavision Sensor Product Page (China). 2025. Retrieved from https:\/\/www.prophesee-cn.com\/event-based-sensor-genx320\/"},{"key":"e_1_3_2_49_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-2724-4_2"},{"key":"e_1_3_2_50_2","unstructured":"inivation. 2025. Retrieved from https:\/\/inivation.com\/"},{"key":"e_1_3_2_51_2","unstructured":"prophesee. 2025. Retrieved from https:\/\/www.prophesee-cn.com\/"},{"key":"e_1_3_2_52_2","unstructured":"Lucid Vision Labs - Official Website (China). 2025. Retrieved from http:\/\/thinklucid.cn\/"},{"key":"e_1_3_2_53_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2018.2800793"},{"key":"e_1_3_2_54_2","unstructured":"Mustafa Sakhai Szymon Mazurek Jakub Caputa Jan K. Argasi\u0144ski and Maciej Wielgosz. 2024. Pedestrian intention prediction in Adverse Weather Conditions with Spiking Neural Networks and Dynamic Vision Sensors. (2024). arXiv:arXiv:2406.00473. Retrieved from https:\/\/arxiv.org\/abs\/2406.00473"},{"key":"e_1_3_2_55_2","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294515"},{"key":"e_1_3_2_56_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3068942"},{"key":"e_1_3_2_57_2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636728"},{"key":"e_1_3_2_58_2","doi-asserted-by":"publisher","DOI":"10.1109\/lra.2022.3186770"},{"key":"e_1_3_2_59_2","first-page":"16639","article-title":"Learning to detect objects with a 1 megapixel event camera","volume":"33","author":"Perot Etienne","year":"2020","unstructured":"Etienne Perot, Pierre De Tournemire, Davide Nitti, Jonathan Masci, and Amos Sironi. 2020. Learning to detect objects with a 1 megapixel event camera. Advances in Neural Information Processing Systems 33 (2020), 16639\u201316652.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_60_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01280"},{"key":"e_1_3_2_61_2","unstructured":"Aayush Atul Verma Bharatesh Chakravarthi Arpitsinh Vaghela Hua Wei and Yezhou Yang. 2024. eTraM: Event-based Traffic Monitoring Dataset. (2024). arXiv:arXiv:2403.19976. Retrieved from https:\/\/arxiv.org\/abs\/2403.19976"},{"key":"e_1_3_2_62_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00313"},{"key":"e_1_3_2_63_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02358"},{"key":"e_1_3_2_64_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00011"},{"key":"e_1_3_2_65_2","doi-asserted-by":"publisher","DOI":"10.1177\/0278364917691115"},{"key":"e_1_3_2_66_2","unstructured":"Wenbin Li Sajad Saeedi John McCormac Ronald Clark Dimos Tzoumanikas Qing Ye Yuzhong Huang Rui Tang and Stefan Leutenegger. 2018. Interiornet: Mega-scale multi-sensor photo-realistic indoor scenes dataset. arXiv:1809.00716. Retrieved from https:\/\/arxiv.org\/abs\/1809.00716. (2018)."},{"key":"e_1_3_2_67_2","doi-asserted-by":"publisher","DOI":"10.1109\/SIMPAR.2016.7862386"},{"key":"e_1_3_2_68_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00144"},{"key":"e_1_3_2_69_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10609864"},{"key":"e_1_3_2_70_2","unstructured":"Video to Event Simulator. 2025. Retrieved from https:\/\/docs.prophesee.ai\/stable\/samples\/modules\/core_ml\/viz_video_to_event_simulator.html"},{"key":"e_1_3_2_71_2","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00574"},{"key":"e_1_3_2_72_2","doi-asserted-by":"publisher","DOI":"10.1109\/NICE61972.2024.10549580"},{"key":"e_1_3_2_73_2","doi-asserted-by":"publisher","DOI":"10.1117\/12.3053238"},{"key":"e_1_3_2_74_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW67362.2025.00506"},{"key":"e_1_3_2_75_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73027-6_18"},{"key":"e_1_3_2_76_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72624-8_27"},{"key":"e_1_3_2_77_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-024-02197-2"},{"key":"e_1_3_2_78_2","doi-asserted-by":"crossref","unstructured":"Nealson Li Muya Chang and Arijit Raychowdhury. 2024. E-Gaze: Gaze estimation with event camera. IEEE Transactions on Pattern Analysis and Machine Intelligence 46 7 (2024) 4796\u20134811.","DOI":"10.1109\/TPAMI.2024.3359606"},{"key":"e_1_3_2_79_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72946-1_10"},{"key":"e_1_3_2_80_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3223020"},{"key":"e_1_3_2_81_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2024.3380255"},{"key":"e_1_3_2_82_2","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2024.3355370"},{"key":"e_1_3_2_83_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2024.106415"},{"key":"e_1_3_2_84_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00154"},{"key":"e_1_3_2_85_2","doi-asserted-by":"crossref","unstructured":"Mathias Gehrig Manasi Muglikar and Davide Scaramuzza. 2024. Dense continuous-time optical flow from event cameras. IEEE Transactions on Pattern Analysis and Machine Intelligence 46 7 (2024) 4736\u20134746.","DOI":"10.1109\/TPAMI.2024.3361671"},{"key":"e_1_3_2_86_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72907-2_10"},{"key":"e_1_3_2_87_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02503"},{"key":"e_1_3_2_88_2","doi-asserted-by":"crossref","unstructured":"Ziwei Wang Timothy Molloy Pieter Van Goor and Robert Mahony. 2024. Asynchronous blob tracker for event cameras. IEEE Transactions on Robotics 40 (2024) 4750\u20134767.","DOI":"10.1109\/TRO.2024.3454410"},{"key":"e_1_3_2_89_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3202659"},{"key":"e_1_3_2_90_2","doi-asserted-by":"publisher","DOI":"10.1109\/BIOROB.2016.7523452"},{"key":"e_1_3_2_91_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2574707"},{"issue":"1","key":"e_1_3_2_92_2","first-page":"15","article-title":"\\(O (N)\\)  O (N)-space spatiotemporal filter for reducing noise in neuromorphic vision sensors","volume":"9","author":"Khodamoradi Alireza","year":"2018","unstructured":"Alireza Khodamoradi and Ryan Kastner. 2018. \\(O (N)\\) O (N)-space spatiotemporal filter for reducing noise in neuromorphic vision sensors. IEEE Transactions on Emerging Topics in Computing 9, 1 (2018), 15\u201323.","journal-title":"IEEE Transactions on Emerging Topics in Computing"},{"key":"e_1_3_2_93_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3152999"},{"key":"e_1_3_2_94_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00652"},{"key":"e_1_3_2_95_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00177"},{"key":"e_1_3_2_96_2","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548048"},{"key":"e_1_3_2_97_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02422"},{"key":"e_1_3_2_98_2","doi-asserted-by":"publisher","DOI":"10.3390\/app10062024"},{"key":"e_1_3_2_99_2","first-page":"21","volume-title":"Proceedings of the International Symposium on Secure-Life Electronics, Advanced Electronics for Quality Life and Society","volume":"1","author":"Delbruck Tobi","year":"2008","unstructured":"Tobi Delbruck. 2008. Frame-free dynamic digital vision. In Proceedings of the International Symposium on Secure-Life Electronics, Advanced Electronics for Quality Life and Society, Vol. 1. Citeseer, 21\u201326."},{"key":"e_1_3_2_100_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-27272-2_35"},{"key":"e_1_3_2_101_2","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2014.2347355"},{"key":"e_1_3_2_102_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.vlsi.2021.04.006"},{"key":"e_1_3_2_103_2","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS.2015.7168735"},{"issue":"11","key":"e_1_3_2_104_2","first-page":"8261","article-title":"Guided event filtering: Synergy between intensity images and neuromorphic events for high performance imaging","volume":"44","author":"Duan Peiqi","year":"2021","unstructured":"Peiqi Duan, Zihao W. Wang, Boxin Shi, Oliver Cossairt, Tiejun Huang, and Aggelos K. Katsaggelos. 2021. Guided event filtering: Synergy between intensity images and neuromorphic events for high performance imaging. IEEE T-PAMI 44, 11 (2021), 8261\u20138275.","journal-title":"IEEE T-PAMI"},{"key":"e_1_3_2_105_2","unstructured":"Ciyu Ruan Ruishan Guo Zihang Gong Jingao Xu Wenhan Yang and Xinlei Chen. 2025. PRE-Mamba: A 4D state space model for ultra-high-frequent event camera deraining. arXiv:2505.05307. Retrieved from https:\/\/arxiv.org\/abs\/2505.05307. (2025)."},{"key":"e_1_3_2_106_2","doi-asserted-by":"publisher","DOI":"10.1145\/3636534.3694737"},{"key":"e_1_3_2_107_2","doi-asserted-by":"publisher","DOI":"10.1117\/12.2305260"},{"key":"e_1_3_2_108_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01263"},{"key":"e_1_3_2_109_2","first-page":"200","volume-title":"Proceedings of the European Conference on Computer Vision","author":"Jiang Bin","year":"2024","unstructured":"Bin Jiang, Bo Xiong, Bohan Qu, M. Salman Asif, You Zhou, and Zhan Ma. 2024. EDformer: Transformer-based event denoising across varied noise levels. In Proceedings of the European Conference on Computer Vision. Springer, 200\u2013216."},{"key":"e_1_3_2_110_2","unstructured":"Ciyu Ruan Zihang Gong Ruishan Guo Jingao Xu and Xinlei Chen. 2025. EDmamba: A simple yet effective event denoising method with state space model. arXiv:2505.05391. Retrieved from https:\/\/arxiv.org\/abs\/2505.05391. (2025)."},{"key":"e_1_3_2_111_2","doi-asserted-by":"publisher","DOI":"10.5244\/C.2.23"},{"key":"e_1_3_2_112_2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2016.7759610"},{"issue":"2","key":"e_1_3_2_113_2","first-page":"407","article-title":"Event-based visual flow","volume":"25","author":"Benosman Ryad","year":"2013","unstructured":"Ryad Benosman, Charles Clercq, Xavier Lagorce, Sio-Hoi Ieng, and Chiara Bartolozzi. 2013. Event-based visual flow. IEEE T-NNLS 25, 2 (2013), 407\u2013417.","journal-title":"IEEE T-NNLS"},{"key":"e_1_3_2_114_2","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2018.00080"},{"key":"e_1_3_2_115_2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS47612.2022.9981451"},{"key":"e_1_3_2_116_2","first-page":"3055","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Gao Yuan","year":"2024","unstructured":"Yuan Gao, Yuqing Zhu, Xinjun Li, Yimin Du, and Tianzhu Zhang. 2024. SD2Event: Self-supervised learning of dynamic detectors and contextual descriptors for event cameras. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 3055\u20133064."},{"key":"e_1_3_2_117_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01209-w"},{"key":"e_1_3_2_118_2","first-page":"1658","volume-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision","author":"Seok Hochang","year":"2020","unstructured":"Hochang Seok and Jongwoo Lim. 2020. Robust feature tracking in dvs event stream using b\u00e9zier mapping. In Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision. 1658\u20131667."},{"key":"e_1_3_2_119_2","unstructured":"Jason Chui Simon Klenk and Daniel Cremers. 2021. Event-based feature tracking in continuous time with sliding window optimization. arXiv:2107.04536. Retrieved from https:\/\/arxiv.org\/abs\/2107.04536"},{"key":"e_1_3_2_120_2","unstructured":"Zexiang Yi Jing Lian Yunliang Qi Zhaofei Yu Huajin Tang Yide Ma and Jizhao Liu. 2023. Deep pulse-coupled neural networks. arXiv:2401.08649. Retrieved from https:\/\/arxiv.org\/abs\/2401.08649"},{"key":"e_1_3_2_121_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3426469"},{"key":"e_1_3_2_122_2","doi-asserted-by":"crossref","unstructured":"Elias Mueggler Chiara Bartolozzi and Davide Scaramuzza. 2017. Fast event-based corner detection. (2017).","DOI":"10.5244\/C.31.33"},{"key":"e_1_3_2_123_2","doi-asserted-by":"publisher","DOI":"10.5244\/C.34.164"},{"key":"e_1_3_2_124_2","unstructured":"Philippe Chiberre Etienne Perot Amos Sironi and Vincent Lepetit. 2022. Long-lived accurate keypoints in event streams. arXiv:2209.10385. Retrieved from https:\/\/arxiv.org\/abs\/2209.10385. (2022)."},{"key":"e_1_3_2_125_2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8968491"},{"key":"e_1_3_2_126_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9412314"},{"key":"e_1_3_2_127_2","doi-asserted-by":"publisher","DOI":"10.23919\/MVA51890.2021.9511407"},{"key":"e_1_3_2_128_2","doi-asserted-by":"publisher","DOI":"10.3390\/s20061600"},{"key":"e_1_3_2_129_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.126805"},{"key":"e_1_3_2_130_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3241201"},{"key":"e_1_3_2_131_2","doi-asserted-by":"crossref","unstructured":"Paul J. Best and Neil D. McKay. 1992. A method for registration of 3-D shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14 2 (1992) 239\u2013256.","DOI":"10.1109\/34.121791"},{"key":"e_1_3_2_132_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989517"},{"key":"e_1_3_2_133_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197341"},{"key":"e_1_3_2_134_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01795"},{"key":"e_1_3_2_135_2","unstructured":"Hongwei Ren Jiadong Zhu Yue Zhou Haotian FU Yulong Huang and Bojun Cheng. 2024. A Simple and Effective Point-based Network for Event Camera 6-DOFs Pose Relocalization. (2024). arXiv:arXiv:2403.19412. Retrieved from https:\/\/arxiv.org\/abs\/2403.19412"},{"key":"e_1_3_2_136_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2023.3339432"},{"key":"e_1_3_2_137_2","unstructured":"Kuanxu Hou Delei Kong Junjie Jiang Hao Zhuang Xinjie Huang and Zheng Fang. 2022. FE-fusion-VPR: Attention-based multi-scale network architecture for visual place recognition by fusing frames and events. (2022). arXiv:arXiv:2211.12244. Retrieved from https:\/\/arxiv.org\/abs\/2211.12244"},{"key":"e_1_3_2_138_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88682-2_6"},{"key":"e_1_3_2_139_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2007.09.014"},{"key":"e_1_3_2_140_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"e_1_3_2_141_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15561-1_56"},{"key":"e_1_3_2_142_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2024.3440099"},{"key":"e_1_3_2_143_2","doi-asserted-by":"crossref","unstructured":"Xiangyuan Wang Kuangyi Chen Wen Yang Lei Yu Yannan Xing and Huai Yu. 2024. FE-DeTr: Keypoint Detection and Tracking in Low-quality Image Frames with Events. (2024). arXiv:arXiv:2403.11662. Retrieved from https:\/\/arxiv.org\/abs\/2403.11662","DOI":"10.1109\/ICRA57147.2024.10610579"},{"key":"e_1_3_2_144_2","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2018.00407"},{"key":"e_1_3_2_145_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00638"},{"key":"e_1_3_2_146_2","first-page":"12292","article-title":"Event cameras, contrast maximization and reward functions: An analysis","author":"Stoffregen Timo","year":"2019","unstructured":"Timo Stoffregen and Lindsay Kleeman. 2019. Event cameras, contrast maximization and reward functions: An analysis. Proceedings of the IEEE\/CVF CVPR (2019), 12292\u201312300. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:198908810","journal-title":"Proceedings of the IEEE\/CVF CVPR"},{"key":"e_1_3_2_147_2","unstructured":"Yilun Wu Federico Paredes-Vall\u00e9s and Guido C. H. E. de Croon. 2024. Lightweight Event-based Optical Flow Estimation via Iterative Deblurring. (2024). arXiv:arXiv:2211.13726. Retrieved from https:\/\/arxiv.org\/abs\/2211.13726"},{"key":"e_1_3_2_148_2","unstructured":"Yutian Chen Shi Guo Fangzheng Yu Feng Zhang Jinwei Gu and Tianfan Xue. 2024. Event-Based Motion Magnification. (2024). arXiv:arXiv:2402.11957. Retrieved from https:\/\/arxiv.org\/abs\/2402.11957"},{"key":"e_1_3_2_149_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00124"},{"key":"e_1_3_2_150_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00398"},{"key":"e_1_3_2_151_2","doi-asserted-by":"crossref","unstructured":"Simon Schaefer Daniel Gehrig and Davide Scaramuzza. 2022. AEGNN: Asynchronous Event-based Graph Neural Networks. (2022). arXiv:arXiv:2203.17149. Retrieved from https:\/\/arxiv.org\/abs\/2203.17149","DOI":"10.1109\/CVPR52688.2022.01205"},{"key":"e_1_3_2_152_2","doi-asserted-by":"publisher","DOI":"10.1177\/0278364914554813"},{"key":"e_1_3_2_153_2","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2015.XI.001"},{"key":"e_1_3_2_154_2","first-page":"2761","article-title":"Event-based, 6-DOF pose tracking for high-speed maneuvers","author":"Mueggler Elias","year":"2014","unstructured":"Elias Mueggler, Basil Huber, and Davide Scaramuzza. 2014. Event-based, 6-DOF pose tracking for high-speed maneuvers. 2014 IEEE\/RSJ International Conference on Intelligent Robots and Systems (2014), 2761\u20132768. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:11454240","journal-title":"2014 IEEE\/RSJ International Conference on Intelligent Robots and Systems"},{"key":"e_1_3_2_155_2","first-page":"4564","article-title":"Fast localization and tracking using event sensors","author":"Yuan Wenzhen","year":"2016","unstructured":"Wenzhen Yuan and Srikumar Ramalingam. 2016. Fast localization and tracking using event sensors. IEEE ICRA (2016), 4564\u20134571. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:1272321","journal-title":"IEEE ICRA"},{"key":"e_1_3_2_156_2","first-page":"1","article-title":"Embedded event-based visual odometry","author":"Bertrand J. L.","year":"2020","unstructured":"J. L. Bertrand, Arda Yi\u011fit, and Sylvain Durand. 2020. Embedded event-based visual odometry. 2020 6th International Conference on Event-Based Control, Communication, and Signal Processing (EBCCSP) (2020), 1\u20138. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:229704037","journal-title":"2020 6th International Conference on Event-Based Control, Communication, and Signal Processing (EBCCSP)"},{"key":"e_1_3_2_157_2","first-page":"16","article-title":"Low-latency visual odometry using event-based feature tracks","author":"Kueng Beat","year":"2016","unstructured":"Beat Kueng, Elias Mueggler, Guillermo Gallego, and Davide Scaramuzza. 2016. Low-latency visual odometry using event-based feature tracks. 2016 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS) (2016), 16\u201323. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:7884141","journal-title":"2016 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)"},{"key":"e_1_3_2_158_2","doi-asserted-by":"publisher","DOI":"10.1109\/ROBIO49542.2019.8961878"},{"key":"e_1_3_2_159_2","first-page":"15","article-title":"SVO: Fast semi-direct monocular visual odometry","author":"Forster Christian","year":"2014","unstructured":"Christian Forster, Matia Pizzoli, and Davide Scaramuzza. 2014. SVO: Fast semi-direct monocular visual odometry. IEEE ICRA (2014), 15\u201322. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:206850490","journal-title":"IEEE ICRA"},{"key":"e_1_3_2_160_2","doi-asserted-by":"publisher","DOI":"10.1109\/ROBIO.2012.6491077"},{"key":"e_1_3_2_161_2","doi-asserted-by":"crossref","unstructured":"William Chamorro Joan Sol\u00e0 and J. Andrade-Cetto. 2022. Event-based line SLAM in real-time. IEEE Robotics and Automation Letters 7 3 (2022) 8146\u20138153. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:250154588","DOI":"10.1109\/LRA.2022.3187266"},{"key":"e_1_3_2_162_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-017-1050-6"},{"key":"e_1_3_2_163_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-39402-7_14"},{"key":"e_1_3_2_164_2","article-title":"Continuous-time trajectory estimation for event-based vision sensors","author":"Mueggler Elias","year":"2015","unstructured":"Elias Mueggler, Guillermo Gallego, and Davide Scaramuzza. 2015. Continuous-time trajectory estimation for event-based vision sensors. Robotics: Science and Systems XI (2015). Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:14725680","journal-title":"Robotics: Science and Systems XI"},{"key":"e_1_3_2_165_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9811943"},{"key":"e_1_3_2_166_2","first-page":"5863","article-title":"IDOL: A framework for IMU-DVS odometry using lines","author":"Gentil C\u00e9dric Le","year":"2020","unstructured":"C\u00e9dric Le Gentil, Florian Tschopp, Ignacio Alzugaray, Teresa Vidal-Calleja, Roland Y. Siegwart, and Juan I. Nieto. 2020. IDOL: A framework for IMU-DVS odometry using lines. 2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS) (2020), 5863\u20135870. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:221112528","journal-title":"2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)"},{"key":"e_1_3_2_167_2","first-page":"4935","article-title":"Spatiotemporal registration for event-based visual odometry","author":"Liu Daqi","year":"2021","unstructured":"Daqi Liu, \u00c1lvaro Parra, and Tat-Jun Chin. 2021. Spatiotemporal registration for event-based visual odometry. IEEE\/CVF CVPR (2021), 4935\u20134944. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:232170519","journal-title":"IEEE\/CVF CVPR"},{"key":"e_1_3_2_168_2","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS.2010.5536970"},{"key":"e_1_3_2_169_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2013.2259038"},{"key":"e_1_3_2_170_2","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2014.2313565"},{"key":"e_1_3_2_171_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.1254642"},{"key":"e_1_3_2_172_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2017.01.003"},{"key":"e_1_3_2_173_2","doi-asserted-by":"publisher","DOI":"10.1109\/MM.2018.112130359"},{"key":"e_1_3_2_174_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-019-1424-8"},{"issue":"1","key":"e_1_3_2_175_2","article-title":"Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip","volume":"15","author":"Yao Man","year":"2024","unstructured":"Man Yao, Ole Richter, Guangshe Zhao, Ning Qiao, Yannan Xing, Dingheng Wang, Tianxiang Hu, Wei Fang, Tugba Demirci, Michele De Marchi, et\u00a0al. 2024. Spike-based dynamic computing with asynchronous sensing-computing neuromorphic chip. Nature Communications 15, 1 (2024), 4464.","journal-title":"Nature Communications"},{"key":"e_1_3_2_176_2","first-page":"246","article-title":"A composable dynamic sparse dataflow architecture for efficient event-based vision processing on FPGA","author":"Gao Yizhao","year":"2024","unstructured":"Yizhao Gao, Baoheng Zhang, Yuhao Ding, and Hayden Kwok-Hay So. 2024. A composable dynamic sparse dataflow architecture for efficient event-based vision processing on FPGA. Computing Research Repository (2024), 246\u2013257.","journal-title":"Computing Research Repository"},{"key":"e_1_3_2_177_2","doi-asserted-by":"crossref","unstructured":"Hao Cao Jingao Xu Danyang Li Zheng Yang and Yunhao Liu. 2024. EventBoost: Event-based acceleration platform for real-time drone localization and tracking. In IEEE INFOCOM 2024-IEEE Conference on Computer Communications. IEEE 1851\u20131859.","DOI":"10.1109\/INFOCOM52122.2024.10621101"},{"key":"e_1_3_2_178_2","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN60899.2024.10650320"},{"key":"e_1_3_2_179_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSI.2024.3387998"},{"key":"e_1_3_2_180_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2852335"},{"key":"e_1_3_2_181_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP40778.2020.9191148"},{"key":"e_1_3_2_182_2","doi-asserted-by":"publisher","DOI":"10.23919\/DATE54114.2022.9774592"},{"key":"e_1_3_2_183_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2015.2474396"},{"key":"e_1_3_2_184_2","doi-asserted-by":"publisher","DOI":"10.1145\/3020078.3021745"},{"key":"e_1_3_2_185_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2023.07.017"},{"key":"e_1_3_2_186_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3156653"},{"key":"e_1_3_2_187_2","unstructured":"Mingjun Li Jianlei Yang Yingjie Qi Meng Dong Yuhao Yang Runze Liu Weitao Pan Bei Yu and Weisheng Zhao. 2022. Eventor: An Efficient Event-Based Monocular Multi-View Stereo Accelerator on FPGA Platform. (2022). arXiv:arXiv:2203.15439. Retrieved from https:\/\/arxiv.org\/abs\/2203.15439"},{"key":"e_1_3_2_188_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9560881"},{"key":"e_1_3_2_189_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-023-01937-0"},{"key":"e_1_3_2_190_2","doi-asserted-by":"crossref","unstructured":"Riccardo Santambrogio Marco Cannici and Matteo Matteucci. 2024. FARSE-CNN: Fully asynchronous recurrent and sparse event-based CNN. In European Conference on Computer Vision. Springer 1\u201318.","DOI":"10.1007\/978-3-031-72949-2_1"},{"key":"e_1_3_2_191_2","doi-asserted-by":"crossref","unstructured":"Yuetong Fang Ziqing Wang Lingfeng Zhang Jiahang Cao Honglei Chen and Renjing Xu. 2024. Spiking wavelet transformer. In European Conference on Computer Vision. Springer 19\u201337.","DOI":"10.1007\/978-3-031-73116-7_2"},{"key":"e_1_3_2_192_2","doi-asserted-by":"crossref","unstructured":"Zhongyang Ren Bangyan Liao Delei Kong Jinghang Li Peidong Liu Laurent Kneip Guillermo Gallego and Yi Zhou. 2024. Motion and structure from event-based normal flow. In European Conference on Computer Vision. Springer 108\u2013125.","DOI":"10.1007\/978-3-031-72992-8_7"},{"key":"e_1_3_2_193_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01032"},{"key":"e_1_3_2_194_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2023.3269780"},{"key":"e_1_3_2_195_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i2.25298"},{"key":"e_1_3_2_196_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01383"},{"key":"e_1_3_2_197_2","first-page":"105552","article-title":"E-Motion: Future motion simulation via event sequence diffusion","volume":"37","author":"Wu Song","year":"2024","unstructured":"Song Wu, Zhiyu Zhu, Junhui Hou, Guangming Shi, and Jinjian Wu. 2024. E-Motion: Future motion simulation via event sequence diffusion. Advances in Neural Information Processing Systems 37 (2024), 105552\u2013105582.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_198_2","unstructured":"Qianang Zhou Zhiyu Zhu Junhui Hou Yongjian Deng Youfu Li and Junlin Xiong. 2024. ResFlow: Fine-tuning residual optical flow for event-based high temporal resolution motion estimation. arXiv:2412.09105. Retrieved from https:\/\/arxiv.org\/abs\/2412.09105. (2024)."},{"key":"e_1_3_2_199_2","unstructured":"Qianang Zhou Junhui Hou Meiyi Yang Yongjian Deng Youfu Li and Junlin Xiong. 2025. Spatially-guided temporal aggregation for robust event-RGB optical flow estimation. arXiv:2501.00838. Retrieved from https:\/\/arxiv.org\/abs\/2501.00838. (2025)."},{"key":"e_1_3_2_200_2","unstructured":"Jinghang Li Bangyan Liao Xiuyuan LU Peidong Liu Shaojie Shen and Yi Zhou. 2024. Event-Aided Time-to-Collision Estimation for Autonomous Driving. (2024). arXiv:arXiv:2407.07324. Retrieved from https:\/\/arxiv.org\/abs\/2407.07324"},{"key":"e_1_3_2_201_2","unstructured":"Qianhui Liu Haibo Ruan Dong Xing Huajin Tang and Gang Pan. 2020. Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks. (2020). arXiv:arXiv:2002.06199. Retrieved from https:\/\/arxiv.org\/abs\/2002.06199"},{"key":"e_1_3_2_202_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02101"},{"key":"e_1_3_2_203_2","doi-asserted-by":"crossref","unstructured":"Yansong Peng Hebei Li Yueyi Zhang Xiaoyan Sun and Feng Wu. 2024. Scene Adaptive Sparse Transformer for Event-based Object Detection. (2024). arXiv:arXiv:2404.01882. Retrieved from https:\/\/arxiv.org\/abs\/2404.01882","DOI":"10.1109\/CVPR52733.2024.01589"},{"key":"e_1_3_2_204_2","doi-asserted-by":"crossref","unstructured":"Nitin J. Sanket Chethan M. Parameshwara Chahat Deep Singh Ashwin V. Kuruttukulam Cornelia Ferm\u00fcller Davide Scaramuzza and Yiannis Aloimonos. 2020. EVDodgeNet: Deep Dynamic Obstacle Dodging with Event Cameras. (2020). arXiv:arXiv:1906.02919. Retrieved from https:\/\/arxiv.org\/abs\/1906.02919","DOI":"10.1109\/ICRA40945.2020.9196877"},{"key":"e_1_3_2_205_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3326683"},{"key":"e_1_3_2_206_2","unstructured":"Yongjian Deng Hao Chen Bochen Xie Hai Liu and Youfu Li. 2023. A Dynamic Graph CNN with Cross-Representation Distillation for Event-Based Recognition. (2023). arXiv:arXiv:2302.04177. Retrieved from https:\/\/arxiv.org\/abs\/2302.04177"},{"key":"e_1_3_2_207_2","unstructured":"Yunfan LU Guoqiang Liang Yusheng Wang Lin Wang and Hui Xiong. 2024. UniINR: Event-guided Unified Rolling Shutter Correction Deblurring and Interpolation. (2024). arXiv:arXiv:2305.15078. Retrieved from https:\/\/arxiv.org\/abs\/2305.15078"},{"key":"e_1_3_2_208_2","unstructured":"Chuanzhi Xu Haoxian Zhou Langyi Chen Yuk Ying Chung and Qiang Qu. 2025. Ultralight polarity-split neuromorphic SNN for event-stream super-resolution. arXiv:2508.03244. Retrieved from https:\/\/arxiv.org\/abs\/2508.03244. (2025)."},{"key":"e_1_3_2_209_2","doi-asserted-by":"crossref","unstructured":"Nico Messikommer Daniel Gehrig Antonio Loquercio and Davide Scaramuzza. 2020. Event-based Asynchronous Sparse Convolutional Networks. (2020). arXiv:arXiv:2003.09148. Retrieved from https:\/\/arxiv.org\/abs\/2003.09148","DOI":"10.1007\/978-3-030-58598-3_25"},{"key":"e_1_3_2_210_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00097"},{"key":"e_1_3_2_211_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3312355"},{"key":"e_1_3_2_212_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2016.2647639"},{"key":"e_1_3_2_213_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3148982"},{"key":"e_1_3_2_214_2","doi-asserted-by":"crossref","unstructured":"Yi-Fan Zuo Jiaqi Yang Jiaben Chen Xia Wang Yifu Wang and Laurent Kneip. 2022. DEVO: Depth-Event Camera Visual Odometry in Challenging Conditions. (2022). arXiv:arXiv:2202.02556. Retrieved from https:\/\/arxiv.org\/abs\/2202.02556","DOI":"10.1109\/ICRA46639.2022.9811805"},{"key":"e_1_3_2_215_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2023.3269950"},{"key":"e_1_3_2_216_2","unstructured":"Edd Gent. 2024. Neuromorphic Camera Helps Drones Navigate Without GPS. (2024). Retrieved from https:\/\/spectrum.ieee.org\/africa-engineering-hardware"},{"key":"e_1_3_2_217_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2903179"},{"key":"e_1_3_2_218_2","unstructured":"Xiuyuan Lu Yi Zhou Junkai Niu Sheng Zhong and Shaojie Shen. 2024. Event-based Visual Inertial Velometer. (2024). arXiv:arXiv:2311.18189. Retrieved from https:\/\/arxiv.org\/abs\/2311.18189"},{"key":"e_1_3_2_219_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3061404"},{"key":"e_1_3_2_220_2","unstructured":"Wenpu Li Pian Wan Peng Wang Jinghang Li Yi Zhou and Peidong Liu. 2024. BeNeRF: Neural Radiance Fields from a Single Blurry Image and Event Stream. (2024). arXiv:arXiv:2407.02174. Retrieved from https:\/\/arxiv.org\/abs\/2407.02174"},{"key":"e_1_3_2_221_2","unstructured":"Yuliang Wu Ganchao Tan Jinze Chen Wei Zhai Yang Cao and Zheng-Jun Zha. 2024. Event-based Asynchronous HDR Imaging by Temporal Incident Light Modulation. (2024). arXiv:arXiv:2403.09392. Retrieved from https:\/\/arxiv.org\/abs\/2403.09392"},{"key":"e_1_3_2_222_2","doi-asserted-by":"crossref","unstructured":"Mathias Gehrig and Davide Scaramuzza. 2023. Recurrent Vision Transformers for Object Detection with Event Cameras. (2023). arXiv:arXiv:2212.05598. Retrieved from https:\/\/arxiv.org\/abs\/2212.05598","DOI":"10.1109\/CVPR52729.2023.01334"},{"key":"e_1_3_2_223_2","doi-asserted-by":"publisher","DOI":"10.1145\/3680207.3765594"},{"key":"e_1_3_2_224_2","unstructured":"Xuecheng Chen Jingao Xu Wenhua Ding Haoyang Wang Xinyu Luo Ruiyang Duan Jialong Chen Xueqian Wang Yunhao Liu and Xinlei Chen. 2025. Count every rotation and every rotation counts: Exploring drone dynamics via propeller sensing. arXiv:2511.13100. Retrieved from https:\/\/arxiv.org\/abs\/2511.13100. (2025)."},{"key":"e_1_3_2_225_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2759326"},{"key":"e_1_3_2_226_2","first-page":"7462","article-title":"Learning graph-embedded key-event back-tracing for object tracking in event clouds","volume":"35","author":"Lyu. Zhiyu Zhu, Junhui Hou, and Xianqiang","year":"2022","unstructured":"Zhiyu Zhu, Junhui Hou, and Xianqiang Lyu.2022. Learning graph-embedded key-event back-tracing for object tracking in event clouds. NIPS 35 (2022), 7462\u20137476.","journal-title":"NIPS"},{"key":"e_1_3_2_227_2","doi-asserted-by":"crossref","unstructured":"Nitin J. Sanket Chahat Deep Singh Chethan M. Parameshwara Cornelia Ferm\u00fcller Guido C. H. E. de Croon and Yiannis Aloimonos. 2021. EVPropNet: Detecting Drones By Finding Propellers For Mid-Air Landing And Following. (2021). arXiv:arXiv:2106.15045. Retrieved from https:\/\/arxiv.org\/abs\/2106.15045","DOI":"10.15607\/RSS.2021.XVII.074"},{"key":"e_1_3_2_228_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10611511"},{"key":"e_1_3_2_229_2","article-title":"Modeling state shifting via local-global distillation for event-frame gaze tracking","author":"Zhu Zhiyu","year":"2025","unstructured":"Zhiyu Zhu, Jinhui Hou, Jiading Li, Jinjian Wu, and Junhui Hou. 2025. Modeling state shifting via local-global distillation for event-frame gaze tracking. IEEE Transactions on Mobile Computing 24, 11 (2025), 11614\u201311627.","journal-title":"IEEE Transactions on Mobile Computing"},{"key":"e_1_3_2_230_2","volume-title":"IEEE\/CVF ICCV","author":"Wu. Zhiyu Zhu, Junhui Hou, and Dapeng Oliver","year":"2023","unstructured":"Zhiyu Zhu, Junhui Hou, and Dapeng Oliver Wu.2023. Cross-modal orthogonal high-rank augmentation for rgb-event transformer-trackers. In IEEE\/CVF ICCV."},{"key":"e_1_3_2_231_2","article-title":"Crossei: Boosting motion-oriented object tracking with an event camera","author":"Chen Zhiwen","year":"2025","unstructured":"Zhiwen Chen, Jinjian Wu, Weisheng Dong, Leida Li, and Guangming Shi. 2025. Crossei: Boosting motion-oriented object tracking with an event camera. IEEE Transactions on Image Processing 34 (2025), 73\u201384.","journal-title":"IEEE Transactions on Image Processing"},{"key":"e_1_3_2_232_2","volume-title":"ACM MobiCom","author":"Chen. Xinyu Luo, Haoyang Wang, Ciyu Ruan, Chenxin Liang, Jingao Xu, and Xinlei","year":"2024","unstructured":"Xinyu Luo, Haoyang Wang, Ciyu Ruan, Chenxin Liang, Jingao Xu, and Xinlei Chen.2024. EventTracker: 3D localization and tracking of high-speed object with event and depth fusion. In ACM MobiCom."},{"key":"e_1_3_2_233_2","unstructured":"2025. Prophesee and Tobii partner to develop next-generation event-based eye tracking solution for AR\/VR and smart eyewear. (2025). Retrieved from https:\/\/www.prophesee.ai\/2025\/05\/20\/prophesee-and-tobii-partner-to-develop-next-generation-event-based-eye-tracking-solution-for-ar-vr-and-smart-eyewear\/"},{"key":"e_1_3_2_234_2","volume-title":"IEEE\/CVF WACV","author":"Fix. Timo Stoffregen, Hossein Daraei, Clare Robinson, and Alexander","year":"2022","unstructured":"Timo Stoffregen, Hossein Daraei, Clare Robinson, and Alexander Fix.2022. Event-based kilohertz eye tracking using coded differential lighting. In IEEE\/CVF WACV."},{"key":"e_1_3_2_235_2","unstructured":"saaz.com. 2025. Retrieved from https:\/\/saaz.com\/"},{"key":"e_1_3_2_236_2","unstructured":"neurobus.ai. 2025. Retrieved from https:\/\/neurobus.ai\/"},{"key":"e_1_3_2_237_2","unstructured":"Adarsh Kumar Kosta and Kaushik Roy. 2023. Adaptive-SpikeNet: Event-based Optical Flow Estimation using Spiking Neural Networks with Learnable Neuronal Dynamics. (2023). arXiv:arXiv:2209.11741. Retrieved from https:\/\/arxiv.org\/abs\/2209.11741"},{"key":"e_1_3_2_238_2","doi-asserted-by":"crossref","unstructured":"Wachirawit Ponghiran Chamika Mihiranga Liyanagedera and Kaushik Roy 2023. Event-based Temporally Dense Optical Flow Estimation with Sequential Learning. (2023). arXiv:arXiv:2210.01244. Retrieved from https:\/\/arxiv.org\/abs\/2210.01244","DOI":"10.1109\/ICCV51070.2023.00901"},{"key":"e_1_3_2_239_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00920"},{"key":"e_1_3_2_240_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19797-0_36"},{"key":"e_1_3_2_241_2","doi-asserted-by":"publisher","unstructured":"Shintaro Shiba Yannick Klose Yoshimitsu Aoki and Guillermo Gallego.2024. Secrets of event-based optical flow depth and ego-motion estimation by contrast maximization. IEEE Transactions on Pattern Analysis and Machine Intelligence 46 12 (2024) 7742\u20137759. DOI:10.1109\/TPAMI.2024.3396116","DOI":"10.1109\/TPAMI.2024.3396116"},{"key":"e_1_3_2_242_2","unstructured":"event-based-vision-iot. 2025. Retrieved from https:\/\/www.prophesee.ai\/event-based-vision-iot\/"},{"key":"e_1_3_2_243_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01819"},{"key":"e_1_3_2_244_2","doi-asserted-by":"crossref","unstructured":"Xu Zheng and Lin Wang. 2024. EventDance: Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition. (2024). arXiv:arXiv:2403.14082. Retrieved from https:\/\/arxiv.org\/abs\/2403.14082","DOI":"10.1109\/CVPR52733.2024.01652"},{"key":"e_1_3_2_245_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3054886"},{"key":"e_1_3_2_246_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00058"},{"key":"e_1_3_2_247_2","unstructured":"Emre O. Neftci Hesham Mostafa and Friedemann Zenke. 2019. Surrogate Gradient Learning in Spiking Neural Networks. (2019). arXiv:arXiv:1901.09948. Retrieved from https:\/\/arxiv.org\/abs\/1901.09948"},{"key":"e_1_3_2_248_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3195063"},{"key":"e_1_3_2_249_2","unstructured":"event-based-vision-medical. 2025. Retrieved from https:\/\/www.prophesee.ai\/event-based-vision-medical\/"},{"key":"e_1_3_2_250_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46466-4_21"},{"key":"e_1_3_2_251_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_15"},{"key":"e_1_3_2_252_2","article-title":"High-speed structured light based 3D scanning using an event camera","author":"Huang Xueyan","unstructured":"Xueyan Huang, Yueyi Zhang, and Zhiwei Xiong. 2021. High-speed structured light based 3D scanning using an event camera. Optics Express 29, 22 (2021), 35864\u201335876.","journal-title":"Optics Express"},{"key":"e_1_3_2_253_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00155"},{"key":"e_1_3_2_254_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01216"},{"key":"e_1_3_2_255_2","unstructured":"Shihao Zou Chuan Guo Xinxin Zuo Sen Wang Pengyu Wang Xiaoqin Hu Shoushun Chen Minglun Gong and Li Cheng. 2021. EventHPE: Event-based 3D Human Pose and Shape Estimation. (2021). arXiv:arXiv:2108.06819. Retrieved from https:\/\/arxiv.org\/abs\/2108.06819"},{"key":"e_1_3_2_256_2","unstructured":"Yuxuan Xue Haolong Li Stefan Leutenegger and J\u00f6rg St\u00fcckler. 2022. Event-based Non-Rigid Reconstruction from Contours. (2022). arXiv:arXiv:2210.06270. Retrieved from https:\/\/arxiv.org\/abs\/2210.06270"},{"key":"e_1_3_2_257_2","doi-asserted-by":"crossref","unstructured":"Linglin Jing Yiming Ding Yunpeng Gao Zhigang Wang Xu Yan Dong Wang Gerald Schaefer Hui Fang Bin Zhao and Xuelong Li. 2024. HPL-ESS: Hybrid Pseudo-Labeling for Unsupervised Event-based Semantic Segmentation. (2024). arXiv:arXiv:2403.16788. Retrieved from https:\/\/arxiv.org\/abs\/2403.16788","DOI":"10.1109\/CVPR52733.2024.02182"},{"key":"e_1_3_2_258_2","doi-asserted-by":"crossref","unstructured":"Lingdong Kong Youquan Liu Lai Xing Ng Benoit R. Cottereau and Wei Tsang Ooi. 2024. OpenESS: Event-based Semantic Scene Understanding with Open Vocabularies. (2024). arXiv:arXiv:2405.05259. Retrieved from https:\/\/arxiv.org\/abs\/2405.05259","DOI":"10.1109\/CVPR52733.2024.01485"},{"key":"e_1_3_2_259_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00734"},{"key":"e_1_3_2_260_2","unstructured":"Ruihao Xia Chaoqiang Zhao Meng Zheng Ziyan Wu Qiyu Sun and Yang Tang. 2023. CMDA: Cross-Modality Domain Adaptation for Nighttime Semantic Segmentation. (2023). arXiv:arXiv:2307.15942. Retrieved from https:\/\/arxiv.org\/abs\/2307.15942"},{"key":"e_1_3_2_261_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10611127"},{"key":"e_1_3_2_262_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00373"},{"key":"e_1_3_2_263_2","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2025.3548523"},{"key":"e_1_3_2_264_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01852"},{"key":"e_1_3_2_265_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2018.2793357"},{"key":"e_1_3_2_266_2","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2024.3378443"},{"key":"e_1_3_2_267_2","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2021.3062252"},{"key":"e_1_3_2_268_2","first-page":"55","volume-title":"ECCV","author":"Bao Yuhan","year":"2024","unstructured":"Yuhan Bao, Lei Sun, Yuqin Ma, and Kaiwei Wang. 2024. Temporal-mapping photography for event cameras. In ECCV. Springer, 55\u201372."},{"key":"e_1_3_2_269_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00917"},{"key":"e_1_3_2_270_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.acl-long.1558"},{"key":"e_1_3_2_271_2","first-page":"1","article-title":"Dense depth-map estimation based on fusion of event camera and sparse LiDAR","volume":"71","author":"Cui Mingyue","year":"2022","unstructured":"Mingyue Cui, Yuzhang Zhu, Yechang Liu, Yunchao Liu, Gang Chen, and Kai Huang. 2022. Dense depth-map estimation based on fusion of event camera and sparse LiDAR. IEEE Transactions on Instrumentation and Measurement 71 (2022), 1\u201311.","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"e_1_3_2_272_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02500"},{"key":"e_1_3_2_273_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0129065709002002"},{"issue":"7","key":"e_1_3_2_274_2","first-page":"4281","article-title":"Toward event-based state estimation for neuromorphic event cameras","volume":"68","author":"Liu Xinhui","year":"2022","unstructured":"Xinhui Liu, Meiqi Cheng, Dawei Shi, and Ling Shi. 2022. Toward event-based state estimation for neuromorphic event cameras. IEEE Transactions on Automatic Control 68, 7 (2022), 4281\u20134288.","journal-title":"IEEE Transactions on Automatic Control"}],"container-title":["ACM Computing Surveys"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3786332","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T12:17:59Z","timestamp":1770207479000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3786332"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,4]]},"references-count":273,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2026,6,30]]}},"alternative-id":["10.1145\/3786332"],"URL":"https:\/\/doi.org\/10.1145\/3786332","relation":{},"ISSN":["0360-0300","1557-7341"],"issn-type":[{"value":"0360-0300","type":"print"},{"value":"1557-7341","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,4]]},"assertion":[{"value":"2025-05-16","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-12-11","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-02-04","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}