{"id":"https://openalex.org/W4295682580","doi":"https://doi.org/10.1145/3503161.3548262","title":"mmBody Benchmark: 3D Body Reconstruction Dataset and Analysis for Millimeter Wave Radar","display_name":"mmBody Benchmark: 3D Body Reconstruction Dataset and Analysis for Millimeter Wave Radar","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4295682580","doi":"https://doi.org/10.1145/3503161.3548262"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548262","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548262","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101770129","display_name":"Anjun Chen","orcid":"https://orcid.org/0000-0003-4209-8301"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anjun Chen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100369974","display_name":"Xiangyu Wang","orcid":"https://orcid.org/0000-0001-8718-6941"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyu Wang","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109585715","display_name":"Shaohao Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohao Zhu","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103759007","display_name":"Yanxu Li","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanxu Li","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100726041","display_name":"Jiming Chen","orcid":"https://orcid.org/0000-0003-3155-3145"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiming Chen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052177334","display_name":"Qi Ye","orcid":"https://orcid.org/0000-0003-0328-5075"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Ye","raw_affiliation_strings":["Zhejiang University &amp; Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University &amp; Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.772,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.93376872,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3501","last_page":"3510"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.799828290939331},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6919026374816895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.674294114112854},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6407965421676636},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6011841297149658},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5295758247375488},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5022192001342773},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.46484440565109253},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.4516375660896301},{"id":"https://openalex.org/keywords/extremely-high-frequency","display_name":"Extremely high frequency","score":0.4319421648979187},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1420997679233551},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.13713589310646057}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.799828290939331},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6919026374816895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.674294114112854},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6407965421676636},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6011841297149658},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5295758247375488},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5022192001342773},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.46484440565109253},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.4516375660896301},{"id":"https://openalex.org/C45764600","wikidata":"https://www.wikidata.org/wiki/Q570342","display_name":"Extremely high frequency","level":2,"score":0.4319421648979187},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1420997679233551},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.13713589310646057},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503161.3548262","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548262","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1967554269","https://openalex.org/W2065726711","https://openalex.org/W2483862638","https://openalex.org/W2554247908","https://openalex.org/W2573098616","https://openalex.org/W2583372902","https://openalex.org/W2612706635","https://openalex.org/W2755937803","https://openalex.org/W2768683308","https://openalex.org/W2776330782","https://openalex.org/W2794401018","https://openalex.org/W2798637590","https://openalex.org/W2799062425","https://openalex.org/W2827033964","https://openalex.org/W2906551905","https://openalex.org/W2913017407","https://openalex.org/W2941074488","https://openalex.org/W2949924544","https://openalex.org/W2963043422","https://openalex.org/W2963355540","https://openalex.org/W2963598138","https://openalex.org/W2963995996","https://openalex.org/W2971856312","https://openalex.org/W2979680912","https://openalex.org/W2979856235","https://openalex.org/W2981356320","https://openalex.org/W2981637078","https://openalex.org/W2990165697","https://openalex.org/W2990640172","https://openalex.org/W2995719402","https://openalex.org/W3010205642","https://openalex.org/W3016627481","https://openalex.org/W3028008698","https://openalex.org/W3034543232","https://openalex.org/W3035551320","https://openalex.org/W3035574168","https://openalex.org/W3035708560","https://openalex.org/W3046956326","https://openalex.org/W3047553107","https://openalex.org/W3109995084","https://openalex.org/W3112082645","https://openalex.org/W3167214600","https://openalex.org/W3168718178","https://openalex.org/W3177334024","https://openalex.org/W3184180073","https://openalex.org/W3205220835","https://openalex.org/W4236965008"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W3177020083","https://openalex.org/W2069451901"],"abstract_inverted_index":{"Millimeter":[0],"Ware":[1],"(mmWave)":[2],"Radar":[3,39],"is":[4,43,95,192,203],"gaining":[5],"popularity":[6],"as":[7],"it":[8,42,61],"can":[9,48,170],"work":[10,22],"in":[11,123,131,149],"adverse":[12,195],"environments":[13],"like":[14],"smoke,":[15],"rain,":[16],"snow,":[17],"poor":[18],"lighting,":[19],"etc.":[20],"Prior":[21],"has":[23],"explored":[24],"the":[25,34,50,54,132,158,163,167,176,182,186,189,200,209,212,218,221,225],"possibility":[26],"of":[27,112,162,208,227],"reconstructing":[28],"3D":[29,51,91],"skeletons":[30],"or":[31,80],"meshes":[32],"from":[33,53,143,188,220,229],"noisy":[35],"and":[36,59,98,114,120,126,146,160,211,224],"sparse":[37],"mmWare":[38],"signals.":[40],"However,":[41],"unclear":[44],"how":[45,60],"accurately":[46],"we":[47,137],"reconstruct":[49],"body":[52,92],"mmWave":[55,77,116,168,190,222],"signals":[56,228],"across":[57],"scenes":[58,125],"performs":[62],"compared":[63],"with":[64,83,101,141],"cameras,":[65],"which":[66],"are":[67],"important":[68],"aspects":[69],"needed":[70],"to":[71,104],"be":[72],"considered":[73],"when":[74],"either":[75],"using":[76],"radars":[78],"alone":[79],"combining":[81],"them":[82,148],"cameras.":[84],"To":[85],"answer":[86],"these":[87],"questions,":[88],"an":[89],"automatic":[90],"annotation":[93],"system":[94],"first":[96],"designed":[97],"built":[99],"up":[100],"multiple":[102],"sensors":[103,145],"collect":[105],"a":[106],"large-scale":[107],"dataset.":[108],"The":[109,152],"dataset":[110,210],"consists":[111],"synchronized":[113],"calibrated":[115],"radar":[117,169,191,223],"point":[118,165],"clouds":[119],"RGB(D)":[121,201],"images":[122],"different":[124,144,230],"skeleton/mesh":[127],"annotations":[128],"for":[129],"humans":[130],"scenes.":[133],"With":[134],"this":[135],"dataset,":[136],"train":[138],"state-of-the-art":[139],"methods":[140],"inputs":[142],"test":[147],"various":[150],"scenarios.":[151],"results":[153,213],"demonstrate":[154],"that":[155],"1)":[156],"despite":[157],"noise":[159],"sparsity":[161],"generated":[164],"clouds,":[166],"achieve":[171],"better":[172],"reconstruction":[173,187,219],"accuracy":[174],"than":[175,181],"RGB":[177],"camera":[178,202],"but":[179],"worse":[180],"depth":[183],"camera;":[184],"2)":[185],"affected":[193],"by":[194],"weather":[196],"conditions":[197],"moderately":[198],"while":[199],"severely":[204],"affected.":[205],"Further,":[206],"analysis":[207],"shadow":[214],"insights":[215],"on":[216],"improving":[217],"combination":[226],"sensors.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-16T09:24:06.705377","created_date":"2025-10-10T00:00:00"}
