{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T15:33:17Z","timestamp":1775230397526,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":78,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,7,10]],"date-time":"2023-07-10T00:00:00Z","timestamp":1688947200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Research Foundation, Singapore and Infocomm Media Development Authority under its Future Communications Research & Development Programme","award":["FCP-NTURG-2022-015"],"award-info":[{"award-number":["FCP-NTURG-2022-015"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,7,10]]},"DOI":"10.1145\/3570361.3592517","type":"proceedings-article","created":{"date-parts":[[2023,7,10]],"date-time":"2023-07-10T16:50:12Z","timestamp":1689007812000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":59,"title":["AutoFed: Heterogeneity-Aware Federated Multimodal Learning for Robust Autonomous Driving"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2826-6498","authenticated-orcid":false,"given":"Tianyue","family":"Zheng","sequence":"first","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4990-1729","authenticated-orcid":false,"given":"Ang","family":"Li","sequence":"additional","affiliation":[{"name":"University of Maryland, College Park, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3215-2696","authenticated-orcid":false,"given":"Zhe","family":"Chen","sequence":"additional","affiliation":[{"name":"Fudan University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2952-636X","authenticated-orcid":false,"given":"Hongbo","family":"Wang","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7036-5158","authenticated-orcid":false,"given":"Jun","family":"Luo","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore, Singapore"}]}],"member":"320","published-online":{"date-parts":[[2023,7,10]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset. arXiv preprint arXiv","author":"Barnes Dan","year":"1909","unstructured":"Dan Barnes, Matthew Gadd, Paul Murcutt, Paul Newman, and Ingmar Posner. 2019. The Oxford Radar RobotCar Dataset: A Radar Extension to the Oxford RobotCar Dataset. arXiv preprint arXiv: 1909.01300 (2019). https:\/\/arxiv.org\/pdf\/1909.01300"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1145\/361002.361007","article-title":"Multidimensional Binary Search Trees used for Associative","volume":"18","author":"Bentley Jon Louis","year":"1975","unstructured":"Jon Louis Bentley. 1975. Multidimensional Binary Search Trees used for Associative Searching. Commun. ACM 18, 9 (1975), 509--517.","journal-title":"Searching. Commun. ACM"},{"key":"e_1_3_2_2_3_1","volume-title":"Proc, of the 33rd IEEE\/CVF CVPR. 11682--11692","author":"Bijelic Mario","year":"2020","unstructured":"Mario Bijelic, Tobias Gruber, Fahim Mannan, Florian Kraus, Werner Ritter, Klaus Dietmayer, and Felix Heide. 2020. Seeing through Fog without Seeing Fog: Deep Multimodal Sensor Fusion in Unseen Adverse Weather. In Proc, of the 33rd IEEE\/CVF CVPR. 11682--11692."},{"key":"e_1_3_2_2_4_1","volume-title":"Proc. of the 33rd IEEE\/CVF CVPR. 11621--11631","author":"Caesar Holger","year":"2020","unstructured":"Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom. 2020. nuScenes: A Multimodal Dataset for Autonomous Driving. In Proc. of the 33rd IEEE\/CVF CVPR. 11621--11631."},{"key":"e_1_3_2_2_5_1","volume-title":"Proc. of the 30st IEEE\/CVF CVPR. 1907--1915","author":"Chen Xiaozhi","year":"2017","unstructured":"Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia. 2017. Multi-view 3D Object Detection Network for Autonomous Driving. In Proc. of the 30st IEEE\/CVF CVPR. 1907--1915."},{"key":"e_1_3_2_2_6_1","volume-title":"Proc. of the 27th ACM MobiCom. 392--405","author":"Chen Zhe","year":"2021","unstructured":"Zhe Chen, Tianyue Zheng, and Jun Luo. 2021. MoVi-Fi: Motion-robust Vital Signs Waveform Recovery via Deep Interpreted RF Sensing. In Proc. of the 27th ACM MobiCom. 392--405."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"crossref","unstructured":"Jim Cherian Jun Luo Hongliang Guo Shen-Shyang Ho and Richard Wisbrun. 2016. ParkGauge: Gauging the Occupancy of Parking Garages with Crowdsensed Parking Characteristics. 92-101 pages.","DOI":"10.1109\/MDM.2016.26"},{"key":"e_1_3_2_2_8_1","first-page":"1","article-title":"Taxonomy and Definitions for Terms Related to On-road Motor Vehicle Automated Driving Systems","volume":"3016","author":"SAE On-Road Automated Vehicle Standards Committee et al.","year":"2014","unstructured":"SAE On-Road Automated Vehicle Standards Committee et al. 2014. Taxonomy and Definitions for Terms Related to On-road Motor Vehicle Automated Driving Systems. SAE Standard J 3016 (2014), 1--16.","journal-title":"SAE Standard J"},{"key":"e_1_3_2_2_9_1","volume-title":"Blondel","author":"De Montjoye Yves-Alexandre","year":"2013","unstructured":"Yves-Alexandre De Montjoye, C\u00e9sar A Hidalgo, Michel Verleysen, and Vincent D. Blondel. 2013. Unique in the Crowd: The Privacy Bounds of Human Mobility. Scientific Reports 3, 1 (2013), 1376:1--5."},{"key":"e_1_3_2_2_10_1","volume-title":"Proc. of the 18th ACM SenSys. 517--530","author":"Ding Shuya","year":"2020","unstructured":"Shuya Ding, Zhe Chen, Tianyue Zheng, and Jun Luo. 2020. RF-Net: A Unified Meta-Learning Framework for RF-enabled One-Shot Human Activity Recognition. In Proc. of the 18th ACM SenSys. 517--530."},{"key":"e_1_3_2_2_11_1","volume-title":"Proc. of The 34th NeurIPS. 1--12","author":"Fallah Alireza","year":"2020","unstructured":"Alireza Fallah, Aryan Mokhtari, and Asuman Ozdaglar. 2020. Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach. In Proc. of The 34th NeurIPS. 1--12."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MCOM.2011.6069707","article-title":"Mobile Crowdsensing: Current State and Future Challenges","volume":"49","author":"Ganti Raghu K.","year":"2011","unstructured":"Raghu K. Ganti, Fan Ye, and Hui Lei. 2011. Mobile Crowdsensing: Current State and Future Challenges. IEEE Communications Magazine 49, 11 (2011), 32--39.","journal-title":"IEEE Communications Magazine"},{"key":"e_1_3_2_2_13_1","volume-title":"Proc. of the 25th IEEE\/CVF CVPR. IEEE, 3354--3361","author":"Geiger Andreas","year":"2012","unstructured":"Andreas Geiger, Philip Lenz, and Raquel Urtasun. 2012. Are We Ready for Autonomous Driving? The KITTI Vision Benchmark Suite. In Proc. of the 25th IEEE\/CVF CVPR. IEEE, 3354--3361."},{"key":"e_1_3_2_2_14_1","volume-title":"Fast R-CNN. In Proc. of the 29th IEEE ICCV. 1440--1448","author":"Girshick Ross","year":"2015","unstructured":"Ross Girshick. 2015. Fast R-CNN. In Proc. of the 29th IEEE ICCV. 1440--1448."},{"key":"e_1_3_2_2_15_1","volume-title":"Proc. of the 27th IEEE\/CVF CVPR. 580--587","author":"Girshick Ross","year":"2014","unstructured":"Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik. 2014. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation. In Proc. of the 27th IEEE\/CVF CVPR. 580--587."},{"key":"e_1_3_2_2_16_1","volume-title":"Proc. of the 17th ACM MobiHoc. 261--270","author":"Han Kai","year":"2016","unstructured":"Kai Han, He Huang, and Jun Luo. 2016. Posted Pricing for Robust Crowdsensing. In Proc. of the 17th ACM MobiHoc. 261--270."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"crossref","first-page":"1728","DOI":"10.1109\/TNET.2018.2846569","article-title":"Quality-Aware Pricing for Mobile Crowdsensing","volume":"26","author":"Han Kai","year":"2018","unstructured":"Kai Han, He Huang, and Jun Luo. 2018. Quality-Aware Pricing for Mobile Crowdsensing. IEEE\/ACM Transactions on Networking 26, 4 (2018), 1728--1741.","journal-title":"IEEE\/ACM Transactions on Networking"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1109\/TC.2015.2419658","article-title":"Truthful Scheduling Mechanisms for Powering Mobile Crowd-sensing","volume":"65","author":"Han Kai","year":"2016","unstructured":"Kai Han, Chi Zhang, Jun Luo, Menglan Hu, and Bharadwaj Veeravalli. 2016. Truthful Scheduling Mechanisms for Powering Mobile Crowd-sensing. IEEE Trans. Comput. 65, 1 (2016), 294--307.","journal-title":"IEEE Trans. Comput."},{"key":"e_1_3_2_2_19_1","volume-title":"Proc. of the 29th IEEE\/CVF CVPR. 770--778","author":"He Kaiming","year":"2016","unstructured":"Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In Proc. of the 29th IEEE\/CVF CVPR. 770--778."},{"key":"e_1_3_2_2_20_1","first-page":"12876","article-title":"Fjord: Fair and Accurate Federated Learning under Heterogeneous Targets with Ordered Dropout","volume":"34","author":"Horvath Samuel","year":"2021","unstructured":"Samuel Horvath, Stefanos Laskaridis, Mario Almeida, Ilias Leontiadis, Stylianos Venieris, and Nicholas Lane. 2021. Fjord: Fair and Accurate Federated Learning under Heterogeneous Targets with Ordered Dropout. Advances in Neural Information Processing Systems 34 (2021), 12876--12889.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_21_1","unstructured":"Intel Corporation. 2022. Intel Xeon Gold 6226 Processor. https:\/\/www.intel.com\/content\/www\/xa\/en\/products\/sku\/193957\/intel-xeon-gold-6226-processor-19-25m-cache-2-70-ghz\/specifications.html. Accessed: 2022-07-28."},{"key":"e_1_3_2_2_22_1","volume-title":"Federated Learning for Object Detection in Autonomous Vehicles. In 2021 IEEE Seventh International Conference on Big Data Computing Service and Applications (BigDataService). 107--114","author":"Jallepalli Deepthi","year":"2021","unstructured":"Deepthi Jallepalli, Navya Chennagiri Ravikumar, Poojitha Vurtur Badarinath, Shravya Uchil, and Mahima Agumbe Suresh. 2021. Federated Learning for Object Detection in Autonomous Vehicles. In 2021 IEEE Seventh International Conference on Big Data Computing Service and Applications (BigDataService). 107--114."},{"key":"e_1_3_2_2_23_1","volume-title":"Lidar Light Scattering Augmentation (LISA): Physics-based Simulation of Adverse Weather Conditions for 3D Object Detection. arXiv preprint arXiv:2107.07004","author":"Kilic Velat","year":"2021","unstructured":"Velat Kilic, Deepti Hegde, Vishwanath Sindagi, A Brinton Cooper, Mark A Foster, and Vishal M Patel. 2021. Lidar Light Scattering Augmentation (LISA): Physics-based Simulation of Adverse Weather Conditions for 3D Object Detection. arXiv preprint arXiv:2107.07004 (2021)."},{"key":"e_1_3_2_2_24_1","volume-title":"Federated Learning: Strategies for Improving Communication Efficiency. In NIPS Workshop on Private Multi-Party Machine Learning. 1--10","author":"Kone\u010dn\u1ef3 Jakub","year":"2014","unstructured":"Jakub Kone\u010dn\u1ef3, H Brendan McMahan, Felix X Yu, Peter Richt\u00e1rik, Ananda Theertha Suresh, and Dave Bacon. 2014. Federated Learning: Strategies for Improving Communication Efficiency. In NIPS Workshop on Private Multi-Party Machine Learning. 1--10."},{"key":"e_1_3_2_2_25_1","volume-title":"Waslander","author":"Ku Jason","year":"2018","unstructured":"Jason Ku, Melissa Mozifian, Jungwook Lee, Ali Harakeh, and Steven L. Waslander. 2018. Joint 3D Proposal Generation and Object Detection from View Aggregation. In Proc. of IEEE\/RSJ IROS. 1--8."},{"key":"e_1_3_2_2_26_1","volume-title":"Proc. of the 19th ACM SenSys. 42--55","author":"Li Ang","year":"2021","unstructured":"Ang Li, Jingwei Sun, Xiao Zeng, Mi Zhang, Hai Li, and Yiran Chen. 2021. FedMask: Joint Computation and Communication-efficient Personalized Federated Learning via Heterogeneous Masking. In Proc. of the 19th ACM SenSys. 42--55."},{"key":"e_1_3_2_2_27_1","volume-title":"Proc. of IEEE\/RSJ IROS. 1513--1518","author":"Li Bo","year":"2017","unstructured":"Bo Li. 2017. 3D Fully Convolutional Network for Vehicle Detection in Point Cloud. In Proc. of IEEE\/RSJ IROS. 1513--1518."},{"key":"e_1_3_2_2_28_1","volume-title":"Vehicle Detection from 3D Lidar using Fully Convolutional Network. arXiv preprint arXiv:1608.07916","author":"Li Bo","year":"2016","unstructured":"Bo Li, Tianlei Zhang, and Tian Xia. 2016. Vehicle Detection from 3D Lidar using Fully Convolutional Network. arXiv preprint arXiv:1608.07916 (2016)."},{"key":"e_1_3_2_2_29_1","volume-title":"Proc. of NeurIPS 31","author":"Li Hao","year":"2018","unstructured":"Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer, and Tom Goldstein. 2018. Visualizing the Loss Landscape of Neural Nets. Proc. of NeurIPS 31 (2018)."},{"key":"e_1_3_2_2_30_1","first-page":"429","article-title":"Federated Optimization in Heterogeneous Networks","volume":"2","author":"Li Tian","year":"2020","unstructured":"Tian Li, Anit Kumar Sahu, Manzil Zaheer, Maziar Sanjabi, Ameet Talwalkar, and Virginia Smith. 2020. Federated Optimization in Heterogeneous Networks. Proc. of MLSys 2 (2020), 429--450.","journal-title":"Proc. of MLSys"},{"key":"e_1_3_2_2_31_1","volume-title":"Proc. of the 12th ECCV. 641--656","author":"Liang Ming","year":"2018","unstructured":"Ming Liang, Bin Yang, Shenlong Wang, and Raquel Urtasun. 2018. Deep Continuous Fusion for Multi-sensor 3D Object Detection. In Proc. of the 12th ECCV. 641--656."},{"key":"e_1_3_2_2_32_1","volume-title":"Proc. of the 31st IEEE ICCV. 2980--2988","author":"Lin Tsung-Yi","year":"2017","unstructured":"Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Doll\u00e1r. 2017. Focal Loss for Dense Object Detection. In Proc. of the 31st IEEE ICCV. 2980--2988."},{"key":"e_1_3_2_2_33_1","volume-title":"Proc. of the 8th ECCV. 740--755","author":"Lin Tsung-Yi","year":"2014","unstructured":"Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Doll\u00e1r, and C Lawrence Zitnick. 2014. Microsoft COCO: Common Objects in Context. In Proc. of the 8th ECCV. 740--755."},{"key":"e_1_3_2_2_34_1","volume-title":"Proc. of IEEE\/RSJ IROS. 5973--5980","author":"Liu Meng","year":"2021","unstructured":"Meng Liu and Jianwei Niu. 2021. BEV-Net: A Bird's Eye View Object Detection Network for LiDAR Point Cloud. In Proc. of IEEE\/RSJ IROS. 5973--5980."},{"key":"e_1_3_2_2_35_1","volume-title":"Berg","author":"Liu Wei","year":"2016","unstructured":"Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C. Berg. 2016. SSD: Single Shot Multibox Detector. In Proc. of the 10th ECCV. 21--37."},{"key":"e_1_3_2_2_36_1","volume-title":"Proc. of the 34th AAAI","volume":"34","author":"Liu Yang","year":"2020","unstructured":"Yang Liu, Anbu Huang, Yun Luo, He Huang, Youzhi Liu, Yuanyuan Chen, Lican Feng, Tianjian Chen, Han Yu, and Qiang Yang. 2020. Fed-vision: An Online Visual Object Detection Platform Powered by Federated Learning. In Proc. of the 34th AAAI, Vol. 34. 13172--13179."},{"key":"e_1_3_2_2_37_1","volume-title":"Proc. of the 31st IEEE\/CVF CVPR. 3569--3577","author":"Luo Wenjie","year":"2018","unstructured":"Wenjie Luo, Bin Yang, and Raquel Urtasun. 2018. Fast and Furious: Real Time End-to-end 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net. In Proc. of the 31st IEEE\/CVF CVPR. 3569--3577."},{"key":"e_1_3_2_2_38_1","volume-title":"Proc. of the 20th PMLR AISTATS. 1273--1282","author":"McMahan Brendan","year":"2017","unstructured":"Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y. Arcas. 2017. Communication-efficient Learning of Deep Networks from Decentralized Data. In Proc. of the 20th PMLR AISTATS. 1273--1282."},{"key":"e_1_3_2_2_39_1","unstructured":"Navtech Radar. 2022. ClearWay Intelligent Transport Systems Solution. https:\/\/navtechradar.com\/solutions\/clearway\/. Accessed: 2022-07-28."},{"key":"e_1_3_2_2_40_1","unstructured":"NVIDIA. 2022. Jetson TX2 Module. https:\/\/developer.nvidia.com\/embedded\/jetson-tx2. Accessed: 2022-07-28."},{"key":"e_1_3_2_2_41_1","unstructured":"Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga et al. 2019. PyTorch: An Imperative Style High-Performance Deep Learning Library. arXiv preprint arXiv:1912.01703 (2019)."},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1080\/14786440109462720","article-title":"On Lines and Planes of Closest Fit to Systems of Points in Space","volume":"2","author":"Pearson Karl","year":"1901","unstructured":"Karl Pearson. 1901. On Lines and Planes of Closest Fit to Systems of Points in Space. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science 2, 11 (1901), 559--572.","journal-title":"The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/s10514-009-9115-1","article-title":"Model based Vehicle Detection and Tracking for Autonomous Urban Driving","volume":"26","author":"Petrovskaya Anna","year":"2009","unstructured":"Anna Petrovskaya and Sebastian Thrun. 2009. Model based Vehicle Detection and Tracking for Autonomous Urban Driving. Autonomous Robots 26, 2 (2009), 123--139.","journal-title":"Autonomous Robots"},{"key":"e_1_3_2_2_44_1","volume-title":"Proc. of the 31st IEEE\/CVF CVPR. 918--927","author":"Qi Charles R","unstructured":"Charles R Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J. Guibas. 2018. Frustum Pointnets for 3D Object Detection from RGB-D Data. In Proc. of the 31st IEEE\/CVF CVPR. 918--927."},{"key":"e_1_3_2_2_45_1","volume-title":"Guibas","author":"Qi Charles R.","year":"2017","unstructured":"Charles R. Qi, Hao Su, Kaichun Mo, and Leonidas J. Guibas. 2017. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation. In Proc. of the 30th IEEE\/CVF CVPR. 652--660."},{"key":"e_1_3_2_2_46_1","volume-title":"Proc. of the 34th IEEE\/CVF CVPR. 444--453","author":"Qian Kun","year":"2021","unstructured":"Kun Qian, Shilin Zhu, Xinyu Zhang, and Li Erran Li. 2021. Robust Multimodal Vehicle Detection in Foggy Weather using Complementary Lidar and Radar Signals. In Proc. of the 34th IEEE\/CVF CVPR. 444--453."},{"key":"e_1_3_2_2_47_1","volume-title":"Proc. of the 29th IEEE\/CVF CVPR. 779--788","author":"Redmon Joseph","year":"2016","unstructured":"Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi. 2016. You Only Look Once: Unified, Real-time Object Detection. In Proc. of the 29th IEEE\/CVF CVPR. 779--788."},{"key":"e_1_3_2_2_48_1","volume-title":"Pedro Porto Buarque de Gusmao, and Nicholas Lane","author":"Ur Rehman Yasar Abbas","year":"2022","unstructured":"Yasar Abbas Ur Rehman, Yan Gao, Jiajun Shen, Pedro Porto Buarque de Gusmao, and Nicholas Lane. 2022. Federated Self-supervised Learning for Video Understanding. arXiv preprint arXiv:2207.01975 (2022)."},{"key":"e_1_3_2_2_49_1","volume-title":"Proc. of The 29th NIPS 28","author":"Ren Shaoqing","year":"2015","unstructured":"Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun. 2015. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. Proc. of The 29th NIPS 28 (2015)."},{"key":"e_1_3_2_2_50_1","unstructured":"Scalabel. 2022. Scalabel A Scalable Open-source Web Annotation Tool. https:\/\/www.scalabel.ai\/. Accessed: 2022-07-28."},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/s40518-019-00135-2","article-title":"Mobility and Energy Impacts of Shared Automated Vehicles: A Review of Recent Literature","volume":"6","author":"Shaheen Susan","year":"2019","unstructured":"Susan Shaheen and Mohamed Amine Bouzaghrane. 2019. Mobility and Energy Impacts of Shared Automated Vehicles: A Review of Recent Literature. Current Sustainable\/Renewable Energy Reports 6, 4 (2019), 193--200.","journal-title":"Current Sustainable\/Renewable Energy Reports"},{"key":"e_1_3_2_2_52_1","volume-title":"Proc. of the 32nd IEEE\/CVF CVPR Workshops. 1--10","author":"Simon Martin","year":"2019","unstructured":"Martin Simon, Karl Amende, Andrea Kraus, Jens Honer, Timo Samann, Hauke Kaulbersch, Stefan Milz, and Horst Michael Gross. 2019. Complexer-YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Clouds. In Proc. of the 32nd IEEE\/CVF CVPR Workshops. 1--10."},{"key":"e_1_3_2_2_53_1","volume-title":"Very Deep Convolutional Networks for Large-Scale Image Recognition. arXiv preprint arXiv:1409.1556","author":"Simonyan Karen","year":"2014","unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Very Deep Convolutional Networks for Large-Scale Image Recognition. arXiv preprint arXiv:1409.1556 (2014)."},{"key":"e_1_3_2_2_54_1","volume-title":"Fedspace: An Efficient Federated Learning Framework at Satellites and Ground Stations. arXiv preprint arXiv:2202.01267","author":"So Jinhyun","year":"2022","unstructured":"Jinhyun So, Kevin Hsieh, Behnaz Arzani, Shadi Noghabi, Salman Avestimehr, and Ranveer Chandra. 2022. Fedspace: An Efficient Federated Learning Framework at Satellites and Ground Stations. arXiv preprint arXiv:2202.01267 (2022)."},{"key":"e_1_3_2_2_55_1","volume-title":"Proc. of the 35th IEEE\/CVF CVPR. 10102--10111","author":"Tang Minxue","year":"2022","unstructured":"Minxue Tang, Xuefei Ning, Yitu Wang, Jingwei Sun, Yu Wang, Hai Li, and Yiran Chen. 2022. FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning. In Proc. of the 35th IEEE\/CVF CVPR. 10102--10111."},{"key":"e_1_3_2_2_56_1","volume-title":"Autopilot: Future of Driving. https:\/\/www.tesla.com\/en_SG\/autopilot. Accessed: 2022-07-25.","year":"2022","unstructured":"Tesla. 2022. Autopilot: Future of Driving. https:\/\/www.tesla.com\/en_SG\/autopilot. Accessed: 2022-07-25."},{"key":"e_1_3_2_2_57_1","unstructured":"Toyota Motor Sales U.S.A. Inc. 2022. 2022 Corolla Discover Corolla. Uncover Fun. https:\/\/www.toyota.com\/corolla\/2022\/. Accessed: 2022-07-28."},{"key":"e_1_3_2_2_58_1","volume-title":"Proc. of the 19th ACM SenSys. 15--28","author":"Tu Linlin","year":"2021","unstructured":"Linlin Tu, Xiaomin Ouyang, Jiayu Zhou, Yuze He, and Guoliang Xing. 2021. FedDL: Federated Learning via Dynamic Layer Sharing for Human Activity Recognition. In Proc. of the 19th ACM SenSys. 15--28."},{"key":"e_1_3_2_2_59_1","unstructured":"Uber Technologies Inc. 2022. Self-Driving Perception & Prediction. https:\/\/www.uber.com\/us\/en\/atg\/research-and-development\/perception-and-prediction\/. Accessed: 2022-07-25."},{"key":"e_1_3_2_2_60_1","volume-title":"Flexible Imputation of Missing Data","author":"Buuren Stef Van","unstructured":"Stef Van Buuren. 2018. Flexible Imputation of Missing Data. CRC press."},{"key":"e_1_3_2_2_61_1","volume-title":"Proc. of the 31st NIPS 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is All You Need. Proc. of the 31st NIPS 30 (2017), 1--11."},{"key":"e_1_3_2_2_62_1","unstructured":"Velodyne Lidar Inc. 2022. HDL-32E High Resolution Real-Time 3D Lidar Sensor. https:\/\/velodynelidar.com\/products\/hdl-32e\/. Accessed: 2022-07-28."},{"key":"e_1_3_2_2_63_1","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1109\/JIOT.2016.2594205","article-title":"Privacy-preserving Mechanisms for Crowdsensing: Survey and Research Challenges","volume":"4","author":"Vergara-Laurens Idalides J.","year":"2016","unstructured":"Idalides J. Vergara-Laurens, Luis G. Jaimes, and Miguel A. Labrador. 2016. Privacy-preserving Mechanisms for Crowdsensing: Survey and Research Challenges. IEEE Internet of Things Journal 4, 4 (2016), 855--869.","journal-title":"IEEE Internet of Things Journal"},{"key":"e_1_3_2_2_64_1","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1109\/TMC.2018.2849416","article-title":"Learning-Based Outdoor Localization Exploiting Crowd-Labeled WiFi Hotspots","volume":"18","author":"Wang Jin","year":"2019","unstructured":"Jin Wang, Jun Luo, Sinno Jialin Pan, and Aixin Sun. 2019. Learning-Based Outdoor Localization Exploiting Crowd-Labeled WiFi Hotspots. IEEE Transactions on Mobile Computing 18, 4 (2019), 896--909.","journal-title":"IEEE Transactions on Mobile Computing"},{"key":"e_1_3_2_2_65_1","volume-title":"Proc. of the 36th IEEE INFOCOM. 1--9.","author":"Wang Jin","year":"2017","unstructured":"Jin Wang, Nicholas Tan, Jun Luo, and Sinno Jialin Pan. 2017. WOLoc: WiFi-only outdoor localization using crowdsensed hotspot labels. In Proc. of the 36th IEEE INFOCOM. 1--9."},{"key":"e_1_3_2_2_66_1","unstructured":"Waymo. 2022. We're building the World's Most Experienced Driver. https:\/\/waymo.com\/?ncr. Accessed: 2022-07-25."},{"key":"e_1_3_2_2_67_1","volume-title":"Waze: Navigation & Live Traffic. (https:\/\/www.waze.com\/. Accessed: 2022-07-28.","author":"Limited Waze Mobile","year":"2022","unstructured":"Waze Mobile Limited. 2022. Waze: Navigation & Live Traffic. (https:\/\/www.waze.com\/. Accessed: 2022-07-28."},{"key":"e_1_3_2_2_68_1","volume-title":"Proc. of the 33rd IEEE\/CVF CVPR. 10941--10950","author":"Wei Xi","year":"2020","unstructured":"Xi Wei, Tianzhu Zhang, Yan Li, Yongdong Zhang, and Feng Wu. 2020. Multi-modality Cross Attention Network for Image and Sentence Matching. In Proc. of the 33rd IEEE\/CVF CVPR. 10941--10950."},{"key":"e_1_3_2_2_69_1","unstructured":"Wu Yuxin and Kirillov Alexander and Massa Francisco and Lo Wan-Yen and Girshick Ross. 2022. Detectron2. https:\/\/github.com\/facebookresearch\/detectron2. Accessed: 2022-07-25."},{"key":"e_1_3_2_2_70_1","volume-title":"Proc. of the 31st IEEE\/CVF CVPR. 244--253","author":"Xu Danfei","year":"2018","unstructured":"Danfei Xu, Dragomir Anguelov, and Ashesh Jain. 2018. PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation. In Proc. of the 31st IEEE\/CVF CVPR. 244--253."},{"key":"e_1_3_2_2_71_1","volume-title":"Proc. of the 31st IEEE\/CVF CVPR. 7652--7660","author":"Yang Bin","year":"2018","unstructured":"Bin Yang, Wenjie Luo, and Raquel Urtasun. 2018. PIXOR: Real-time 3D Object Detection from Point Clouds. In Proc. of the 31st IEEE\/CVF CVPR. 7652--7660."},{"key":"e_1_3_2_2_72_1","volume-title":"Proc. of the 18th ACM MobiCom. 173--184","author":"Yang Dejun","year":"2012","unstructured":"Dejun Yang, Guoliang Xue, Xi Fang, and Jian Tang. 2012. Crowdsourcing to Smartphones: Incentive Mechanism Design for Mobile Phone Sensing. In Proc. of the 18th ACM MobiCom. 173--184."},{"key":"e_1_3_2_2_73_1","volume-title":"Proceedings of the 3rd International Conference on Vision, Image and Signal Processing. 1--6.","author":"Yu Peihua","year":"2019","unstructured":"Peihua Yu and Yunfeng Liu. 2019. Federated Object Detection: Optimizing Object Detection Model with Federated Learning. In Proceedings of the 3rd International Conference on Vision, Image and Signal Processing. 1--6."},{"key":"e_1_3_2_2_74_1","volume-title":"Proc. of the 10th IEEE\/ACM DCOSS. 75--82","author":"Zhang Chi","year":"2014","unstructured":"Chi Zhang, Jun Luo, and Jianxin Wu. 2014. A Dual-Sensor Enabled Indoor Localization System with Crowdsensing Spot Survey. In Proc. of the 10th IEEE\/ACM DCOSS. 75--82."},{"key":"e_1_3_2_2_75_1","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1109\/TMC.2014.2319824","article-title":"GROPING: Geomagnetism and cROwdsensing Powered Indoor NaviGation","volume":"14","author":"Zhang Chi","year":"2015","unstructured":"Chi Zhang, Kalyan P. Subbu, Jun Luo, and Jianxin Wu. 2015. GROPING: Geomagnetism and cROwdsensing Powered Indoor NaviGation. IEEE Transactions on Mobile Computing 14, 2 (2015), 387--400.","journal-title":"IEEE Transactions on Mobile Computing"},{"key":"e_1_3_2_2_76_1","doi-asserted-by":"crossref","first-page":"2990","DOI":"10.1109\/TITS.2020.2978438","article-title":"Method and Applications of LiDAR Modeling for Virtual Testing of Intelligent Vehicles","volume":"22","author":"Zhao Jian","year":"2020","unstructured":"Jian Zhao, Yaxin Li, Bing Zhu, Weiwen Deng, and Bohua Sun. 2020. Method and Applications of LiDAR Modeling for Virtual Testing of Intelligent Vehicles. IEEE Transactions on Intelligent Transportation Systems 22, 5 (2020), 2990--3000.","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"e_1_3_2_2_77_1","volume-title":"Proc. of the 20th ACM UbiComp. 70:1--27","author":"Zheng Tianyue","year":"2020","unstructured":"Tianyue Zheng, Zhe Chen, Chao Cai, Jun Luo, and Xu Zhang. 2020. V2iFi: in-Vehicle Vital Sign Monitoring via Compact RF Sensing. In Proc. of the 20th ACM UbiComp. 70:1--27."},{"key":"e_1_3_2_2_78_1","volume-title":"Proc. of the 31st IEEE\/CVF CVPR. 4490--4499","author":"Zhou Yin","year":"2018","unstructured":"Yin Zhou and Oncel Tuzel. 2018. VoxelNet: End-to-End Learning for Point Cloud based 3D Object Detection. In Proc. of the 31st IEEE\/CVF CVPR. 4490--4499."}],"event":{"name":"ACM MobiCom '23: 29th Annual International Conference on Mobile Computing and Networking","location":"Madrid Spain","acronym":"ACM MobiCom '23","sponsor":["SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing"]},"container-title":["Proceedings of the 29th Annual International Conference on Mobile Computing and Networking"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3570361.3592517","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3570361.3592517","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:27Z","timestamp":1750182567000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3570361.3592517"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,10]]},"references-count":78,"alternative-id":["10.1145\/3570361.3592517","10.1145\/3570361"],"URL":"https:\/\/doi.org\/10.1145\/3570361.3592517","relation":{},"subject":[],"published":{"date-parts":[[2023,7,10]]},"assertion":[{"value":"2023-07-10","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}