{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T14:11:05Z","timestamp":1779372665169,"version":"3.53.1"},"reference-count":39,"publisher":"Association for Computing Machinery (ACM)","issue":"6","license":[{"start":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T00:00:00Z","timestamp":1779321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"crossref","award":["2025M771516"],"award-info":[{"award-number":["2025M771516"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Open Project Program of State Key Laboratory of Virtual Reality Technology and Systems, Beihang University","award":["62125305"],"award-info":[{"award-number":["62125305"]}]},{"name":"Natural Science Basis Research Plan in Shaanxi Province of China","award":["2025JC-JCQN-091"],"award-info":[{"award-number":["2025JC-JCQN-091"]}]},{"name":"Technology Innovation Leading Program of Shaanxi","award":["2024QY-SZX-23"],"award-info":[{"award-number":["2024QY-SZX-23"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2026,6,30]]},"abstract":"<jats:p>\n                    Event-based monocular depth estimation is crucial for applications such as autonomous driving, obstacle avoidance, and navigation under high-speed scenarios. Events exhibit a unique and irregular modality. To adapt them to neural networks, some studies convert event streams into event voxels or other frame-like representations. However, these approaches tend to lose the temporal characteristics of events. In this study, we propose a network that aggregates global voxel and per-channel temporal local features of event voxels across the temporal dimension, explicitly extracting events\u2019 temporal information. Furthermore, as noise in events can interfere with the training process and is more difficult to predict than that in images, we utilize the uncertainty estimation module to mitigate the impact of uncertain factors and enhance the robustness of the model. Additionally, we employ multi-level depth features for supervisory training, which improves prediction performance compared to methods relying solely on ground-truth depth supervision. Experiments on open source datasets demonstrate the effectiveness of the proposed method. Our code can be found at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/WuShangjie\/GLUNET\">https:\/\/github.com\/WuShangjie\/GLUNET<\/jats:ext-link>\n                    .\n                  <\/jats:p>","DOI":"10.1145\/3803017","type":"journal-article","created":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T08:41:40Z","timestamp":1774687300000},"page":"1-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["GLU-Net: Global\u2013Local Fusion Network for Event-Based Monocular Depth Estimation via Uncertainty Optimization"],"prefix":"10.1145","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-0810-5754","authenticated-orcid":false,"given":"Shangjie","family":"Wu","sequence":"first","affiliation":[{"name":"School of Software Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3081-8781","authenticated-orcid":false,"given":"Jihua","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China and National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, Xi\u2019an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2717-3669","authenticated-orcid":false,"given":"Zhikuan","family":"Zhou","sequence":"additional","affiliation":[{"name":"BNRist, THUIBCS, BLBCI, School of Software, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9720-826X","authenticated-orcid":false,"given":"Siqi","family":"Li","sequence":"additional","affiliation":[{"name":"BNRist, THUIBCS, BLBCI, School of Software, Tsinghua University, Beijing, China and Yangtze Delta Region Institute, Tsinghua University, Jiaxing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7092-0596","authenticated-orcid":false,"given":"Shaoyi","family":"Du","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Human-Machine Hybrid Augmented Intelligence, National Engineering Research Center for Visual Information and Applications, and Institute of Artificial Intelligence and Robotics, Xi\u2019an Jiaotong University, Xi\u2019an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4971-590X","authenticated-orcid":false,"given":"Yue","family":"Gao","sequence":"additional","affiliation":[{"name":"BNRist, THUIBCS, BLBCI, School of Software, Tsinghua University, Beijing, China and Yangtze Delta Region Institute, Tsinghua University, Jiaxing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,5,21]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46466-4_21"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00407"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2016.2645143"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2018.2793357"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00389"},{"key":"e_1_3_1_7_2","unstructured":"Shuwei Shao Zhongcai Pei Xingming Wu Zhong Liu Weihai Chen and Zhengguo Li. 2023. 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