{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T00:07:43Z","timestamp":1755907663174,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":23,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,1,19]],"date-time":"2024-01-19T00:00:00Z","timestamp":1705622400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,1,19]]},"DOI":"10.1145\/3653781.3653817","type":"proceedings-article","created":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T12:22:26Z","timestamp":1717244546000},"page":"1-8","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A High Precision Reconstruction Method of Point Cloud for Three-dimensional Radar Imaging"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-6673-1410","authenticated-orcid":false,"given":"Yifei","family":"Hu","sequence":"first","affiliation":[{"name":"School of Information and Communication Engineering University of Electronic Science and Technology of China, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0722-970X","authenticated-orcid":false,"given":"Jiahui","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering University of Electronic Science and Technology of China, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8091-9540","authenticated-orcid":false,"given":"Shunjun","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering University of Electronic Science and Technology of China, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3462-3989","authenticated-orcid":false,"given":"Mou","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information and Communication Engineering University of Electronic Science and Technology of China, China"}]}],"member":"320","published-online":{"date-parts":[[2024,6]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0161-6420(03)00496-2"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2006.871582"},{"key":"e_1_3_2_1_3_1","volume-title":"Proceedings of the Asian Conference on Computer Vision. 586\u2013601","author":"Du Hang","year":"2022","unstructured":"Hang Du, Xuejun Yan, Jingjing Wang, Di Xie, and Shiliang Pu. 2022. Point cloud upsampling via cascaded refinement network. In Proceedings of the Asian Conference on Computer Vision. 586\u2013601."},{"key":"e_1_3_2_1_4_1","first-page":"669","article-title":"Multi-directional evolution trend and law analysis of radar ground imaging technology","volume":"8","author":"Jianyu YANG","year":"2019","unstructured":"YANG Jianyu. 2019. Multi-directional evolution trend and law analysis of radar ground imaging technology. Journal of Radars 8, 6 (2019), 669\u2013692.","journal-title":"Journal of Radars"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.3724\/SP.J.1300.2012.20076"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00730"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00459"},{"key":"e_1_3_2_1_8_1","first-page":"387","article-title":"A Cylindrical Scanning Millimeter-Wave 3D Imaging Algorithm Incorporating \u03c9 -K and BP Algorithms","volume":"7","author":"Pengfei Xie","year":"2018","unstructured":"Xie Pengfei, Zhang Lei, and Wu Zhenhua. 2018. A Cylindrical Scanning Millimeter-Wave 3D Imaging Algorithm Incorporating \u03c9 -K and BP Algorithms. Journal of Radars 7, 3 (2018), 387\u2013394.","journal-title":"Journal of Radars"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2018.09.001"},{"key":"e_1_3_2_1_10_1","volume-title":"Proceedings of the IEEE conference on computer vision and pattern recognition. 652\u2013660","author":"Qi R","year":"2017","unstructured":"Charles\u00a0R Qi, Hao Su, Kaichun Mo, and Leonidas\u00a0J Guibas. 2017. Pointnet: Deep learning on point sets for 3d classification and segmentation. In Proceedings of the IEEE conference on computer vision and pattern recognition. 652\u2013660."},{"key":"e_1_3_2_1_11_1","volume-title":"Deep hierarchical feature learning on point sets in a metric space. Advances in neural information processing systems 30","author":"Qi Charles\u00a0Ruizhongtai","year":"2017","unstructured":"Charles\u00a0Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas\u00a0J Guibas. 2017. Pointnet++: Deep hierarchical feature learning on point sets in a metric space. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01151"},{"key":"e_1_3_2_1_13_1","volume-title":"U-net: Convolutional networks for biomedical image segmentation. In Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI 2015: 18th International Conference","author":"Ronneberger Olaf","year":"2015","unstructured":"Olaf Ronneberger, Philipp Fischer, and Thomas Brox. 2015. U-net: Convolutional networks for biomedical image segmentation. In Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18. Springer, 234\u2013241."},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the eurographics workshop on 3D object retrieval, Vol.\u00a010","author":"Savva Manolis","year":"2016","unstructured":"Manolis Savva, Fisher Yu, Hao Su, M Aono, B Chen, D Cohen-Or, W Deng, Hang Su, Song Bai, Xiang Bai, 2016. Shrec16 track: largescale 3d shape retrieval from shapenet core55. In Proceedings of the eurographics workshop on 3D object retrieval, Vol.\u00a010. 13."},{"key":"e_1_3_2_1_15_1","first-page":"664","article-title":"A compressed-aware line array 3D SAR self-focusing imaging algorithm based on semi-positive definite planning","volume":"7","author":"Shunjun Wei","year":"2018","unstructured":"Wei Shunjun, Tian Bokun, Zhang Xiaoling, Shijun, 2018. A compressed-aware line array 3D SAR self-focusing imaging algorithm based on semi-positive definite planning. Journal of Radars 7, 6 (2018), 664\u2013675.","journal-title":"Journal of Radars"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3039534"},{"key":"e_1_3_2_1_17_1","first-page":"6320","article-title":"Snowflake point deconvolution for point cloud completion and generation with skip-transformer","volume":"45","author":"Xiang Peng","year":"2022","unstructured":"Peng Xiang, Xin Wen, Yu-Shen Liu, Yan-Pei Cao, Pengfei Wan, Wen Zheng, and Zhizhong Han. 2022. Snowflake point deconvolution for point cloud completion and generation with skip-transformer. IEEE Transactions on Pattern Analysis and Machine Intelligence 45, 5 (2022), 6320\u20136338.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_3_2_1_18_1","first-page":"485","article-title":"SARMV3D-1.0: SAR Microwave Vision 3D Imaging Dataset","volume":"10","author":"Xiaolan Qiu","year":"2021","unstructured":"Qiu Xiaolan, Jiao Zekun, Peng Lingxiao, Chen Jiankun, Guo Jiayi, Zhou Liangzhong, Chen Longyong, Ding Chibiao, Xu Feng, Dong Qiulei, 2021. SARMV3D-1.0: SAR Microwave Vision 3D Imaging Dataset. Journal of Radars 10, 4 (2021), 485\u2013498.","journal-title":"Journal of Radars"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00029"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00611"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00295"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2018.00088"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2022.3205628","article-title":"SAF-3DNet: Unsupervised AMP-inspired network for 3-D MMW SAR imaging and autofocusing","volume":"60","author":"Zhou Zichen","year":"2022","unstructured":"Zichen Zhou, Shunjun Wei, Hao Zhang, Rong Shen, Mou Wang, Jun Shi, and Xiaoling Zhang. 2022. SAF-3DNet: Unsupervised AMP-inspired network for 3-D MMW SAR imaging and autofocusing. IEEE Transactions on Geoscience and Remote Sensing 60 (2022), 1\u201315.","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"}],"event":{"name":"CVDL 2024: The International Conference on Computer Vision and Deep Learning","acronym":"CVDL 2024","location":"Changsha China"},"container-title":["Proceedings of the International Conference on Computer Vision and Deep Learning"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3653781.3653817","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3653781.3653817","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T15:25:58Z","timestamp":1755876358000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3653781.3653817"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,19]]},"references-count":23,"alternative-id":["10.1145\/3653781.3653817","10.1145\/3653804"],"URL":"https:\/\/doi.org\/10.1145\/3653781.3653817","relation":{},"subject":[],"published":{"date-parts":[[2024,1,19]]},"assertion":[{"value":"2024-06-01","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}