{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T13:48:42Z","timestamp":1763732922139,"version":"3.45.0"},"publisher-location":"New York, NY, USA","reference-count":12,"publisher":"ACM","funder":[{"name":"National Natural Science Foundation of China (NSFC)","award":["62227809","62401024"],"award-info":[{"award-number":["62227809","62401024"]}]},{"name":"Shenzhen Science and Technology Program","award":["JCYJ20241202125910015"],"award-info":[{"award-number":["JCYJ20241202125910015"]}]},{"name":"GuangDong Basic and Applied Basic Research Foundation","award":["2023B0303000019"],"award-info":[{"award-number":["2023B0303000019"]}]},{"name":"State Key Laboratory of Photonics and Communications","award":["2025QZKF09","2025QZKF05"],"award-info":[{"award-number":["2025QZKF09","2025QZKF05"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,11,3]]},"DOI":"10.1145\/3680207.3765597","type":"proceedings-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T13:19:18Z","timestamp":1763731158000},"page":"1222-1224","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Demo: Amodal Instance Segmentation Using MmWave Radar"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-2784-6208","authenticated-orcid":false,"given":"Sutong","family":"Zhang","sequence":"first","affiliation":[{"name":"Peking University Shenzhen Graduate School, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1475-3631","authenticated-orcid":false,"given":"Haobo","family":"Zhang","sequence":"additional","affiliation":[{"name":"Peking University Shenzhen Graduate School, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9196-7414","authenticated-orcid":false,"given":"Shuhao","family":"Zeng","sequence":"additional","affiliation":[{"name":"Peking University Shenzhen Graduate School, Princeton University, State of New Jersey, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3484-1361","authenticated-orcid":false,"given":"Boya","family":"Di","sequence":"additional","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8644-8241","authenticated-orcid":false,"given":"Lingyang","family":"Song","sequence":"additional","affiliation":[{"name":"Peking University Shenzhen Graduate School, Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,11,21]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit. 10632\u201310643","author":"Yang J.","unstructured":"J. Yang, S. Yang, A. W. Gupta, R. Han, L. Fei-Fei, and S. Xie. 2025. Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces. In Proc. IEEE Conf. Comput. Vis. Pattern Recognit. 10632\u201310643."},{"key":"e_1_3_2_1_2_1","volume-title":"Perception and imagination: Amodal perception as mental imagery. Philos. Stud. 150 (Sept","year":"2010","unstructured":"Bence Nanay. 2010. Perception and imagination: Amodal perception as mental imagery. Philos. Stud. 150 (Sept. 2010), 239\u2013254."},{"key":"e_1_3_2_1_3_1","volume-title":"The Importance of Amodal Completion in Everyday Perception. i-Perception 9, 4 (Jul","author":"Nanay B.","year":"2018","unstructured":"B. Nanay. 2018. The Importance of Amodal Completion in Everyday Perception. i-Perception 9, 4 (Jul. 2018), 2041669518788887."},{"key":"e_1_3_2_1_4_1","first-page":"1","article-title":"Toward Weather-Robust 3D Human Body Reconstruction: Millimeter-Wave Radar-Based Dataset, Benchmark, and Multi-Modal Fusion","volume":"35","author":"Chen A.","year":"2025","unstructured":"A. Chen, X. Wang, K. Shi, Y. Huo, J. Chen, and Q. Ye. 2025. Toward Weather-Robust 3D Human Body Reconstruction: Millimeter-Wave Radar-Based Dataset, Benchmark, and Multi-Modal Fusion. IEEE Trans. Circuits Syst. Video Technol. 35, 1 (Jan. 2025), 273\u2013286.","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/COMST.2024.3409556","article-title":"A Survey of mmWave Radar-Based Sensing in Autonomous Vehicles, Smart Homes and Industry","volume":"27","author":"Kong H.","year":"2025","unstructured":"H. Kong, C. Huang, J. Yu, and X. Shen. 2025. A Survey of mmWave Radar-Based Sensing in Autonomous Vehicles, Smart Homes and Industry. IEEE Commun. Surv. Tutor. 27, 1 (Feb. 2025), 463\u2013508.","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","first-page":"10","DOI":"10.3390\/s21103388","article-title":"Pedestrian Detection in Blind Area and Motion Classification Based on Rush-Out Risk Using Micro-Doppler Radar","volume":"21","author":"Hayashi S.","year":"2021","unstructured":"S. Hayashi, K. Saho, D. Isobe, and M. Masugi. 2021. Pedestrian Detection in Blind Area and Motion Classification Based on Rush-Out Risk Using Micro-Doppler Radar. Sensors 21, 10 (May 2021), 3388.","journal-title":"Sensors"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1109\/TIV.2022.3167733","article-title":"Millimeter Wave FMCW RADARs for Perception, Recognition and Localization in Automotive Applications: A Survey","volume":"7","author":"Venon A.","year":"2022","unstructured":"A. Venon, Y. Dupuis, P. Vasseur, and P. Merriaux. 2022. Millimeter Wave FMCW RADARs for Perception, Recognition and Localization in Automotive Applications: A Survey. IEEE Trans. Intell. Veh. 7, 3 (Sept. 2022), 533\u2013555.","journal-title":"IEEE Trans. Intell. Veh."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1049\/cje.2018.08.003","article-title":"CNN based classification of rigid targets in space using radar micro-Doppler signatures","volume":"28","author":"Wang J.","year":"2019","unstructured":"J. Wang, H. Zhu, P. Lei, T. Zheng, and F. Gao. 2019. CNN based classification of rigid targets in space using radar micro-Doppler signatures. Chin. J. Electron. 28, 4 (Jul. 2019), 856\u2013862.","journal-title":"Chin. J. Electron."},{"key":"e_1_3_2_1_9_1","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit. 2434\u20132442","author":"Wei Z.","unstructured":"Z. Wei, Y. Sun, J. Wang, H. Lai, and S. Liu. 2017. Deep Metrics for Person Re-identification. In Proc. IEEE Conf. Comput. Vis. Pattern Recognit. 2434\u20132442."},{"key":"e_1_3_2_1_10_1","volume-title":"Proc. IEEE Int. Conf. Intell. Transp. Syst. 493\u2013498","author":"Zheng L.","unstructured":"L. Zheng, Z. Ma, X. Zhu, B. Tan, S. Li, K. Long, W. Sun, S. Chen, L. Zhang, M. Wan, L. Huang, and J. Bai. 2022. TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving. In Proc. IEEE Int. Conf. Intell. Transp. Syst. 493\u2013498."},{"key":"e_1_3_2_1_11_1","volume-title":"Proc. Int. Conf. 3D Vis. 728\u2013737","author":"Yuan W.","unstructured":"W. Yuan, T. Khot, D. Held, C. Mertz, and M. Hebert. 2018. PCN: Point Completion Network. In Proc. Int. Conf. 3D Vis. 728\u2013737."},{"key":"e_1_3_2_1_12_1","first-page":"12","article-title":"AdaPoinTr: Diverse Point Cloud Completion With Adaptive Geometry-Aware Transformers","volume":"45","author":"Yu X.","year":"2023","unstructured":"X. Yu, Y. Rao, Z. Wang, J. Lu, and J. Zhou. 2023. AdaPoinTr: Diverse Point Cloud Completion With Adaptive Geometry-Aware Transformers. IEEE Trans. Pattern Anal. Mach. Intell. 45, 12 (Dec. 2023), 14114\u201314130.","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"event":{"name":"ACM MOBICOM '25: 31st Annual International Conference on Mobile Computing and Networking","location":"Kerry Hotel, Hong Kong Hong Kong China","acronym":"ACM MOBICOM '25","sponsor":["SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing"]},"container-title":["Proceedings of the 31st Annual International Conference on Mobile Computing and Networking"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3680207.3765597","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T13:26:43Z","timestamp":1763731603000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3680207.3765597"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,3]]},"references-count":12,"alternative-id":["10.1145\/3680207.3765597","10.1145\/3680207"],"URL":"https:\/\/doi.org\/10.1145\/3680207.3765597","relation":{},"subject":[],"published":{"date-parts":[[2025,11,3]]},"assertion":[{"value":"2025-11-21","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}