{"id":"https://openalex.org/W3206230244","doi":"https://doi.org/10.1145/3474085.3475478","title":"MM-Flow","display_name":"MM-Flow","publication_year":2021,"publication_date":"2021-10-17","ids":{"openalex":"https://openalex.org/W3206230244","doi":"https://doi.org/10.1145/3474085.3475478","mag":"3206230244"},"language":"en","primary_location":{"id":"doi:10.1145/3474085.3475478","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475478","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100952126","display_name":"Yiqiang Zhao","orcid":"https://orcid.org/0000-0002-4564-952X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqiang Zhao","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101072074","display_name":"Yiyao Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiyao Zhou","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100618297","display_name":"Rui Chen","orcid":"https://orcid.org/0000-0003-0705-6739"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Chen","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102712165","display_name":"Bin Hu","orcid":"https://orcid.org/0009-0001-0626-423X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Hu","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088429093","display_name":"Xiding Ai","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiding Ai","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3266","last_page":"3274"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9998999834060669,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9984999895095825,"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/point-cloud","display_name":"Point cloud","score":0.7451832890510559},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7172776460647583},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.552825927734375},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5485268235206604},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.5057873725891113},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.4941542446613312},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.43243294954299927},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42141997814178467},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4141748547554016},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3491041958332062},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3055956959724426},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16775014996528625}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7451832890510559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7172776460647583},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.552825927734375},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5485268235206604},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.5057873725891113},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.4941542446613312},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.43243294954299927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42141997814178467},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4141748547554016},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3491041958332062},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3055956959724426},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16775014996528625},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3474085.3475478","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3474085.3475478","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8797217819","display_name":"\u57fa\u4e8e\u8de8\u5c42\u6b21\u751f\u6210\u5bf9\u6297\u7f51\u7edc\u7684\u79fb\u52a8\u7aef\u56fe\u50cf\u8d85\u5206\u8fa8\u7387\u7814\u7a76","funder_award_id":"61871284","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2115579991","https://openalex.org/W2338532005","https://openalex.org/W2342277278","https://openalex.org/W2559882727","https://openalex.org/W2560722161","https://openalex.org/W2609754928","https://openalex.org/W2737234477","https://openalex.org/W2772926850","https://openalex.org/W2795199083","https://openalex.org/W2796426482","https://openalex.org/W2798777114","https://openalex.org/W2890382763","https://openalex.org/W2897003273","https://openalex.org/W2964137676","https://openalex.org/W2964771480","https://openalex.org/W2979750740","https://openalex.org/W2985683375","https://openalex.org/W2986615800","https://openalex.org/W2994631335","https://openalex.org/W2998689703","https://openalex.org/W3034493208","https://openalex.org/W3034584726","https://openalex.org/W3102456204","https://openalex.org/W3104141662","https://openalex.org/W3108944788","https://openalex.org/W4249142012","https://openalex.org/W4249914127","https://openalex.org/W4255556797"],"related_works":["https://openalex.org/W4380150146","https://openalex.org/W3024870410","https://openalex.org/W2410652950","https://openalex.org/W4283773154","https://openalex.org/W3139174110","https://openalex.org/W4289597203","https://openalex.org/W2085630472","https://openalex.org/W1977098485","https://openalex.org/W4285201053","https://openalex.org/W4256612600"],"abstract_inverted_index":{"Point":[0],"cloud":[1,78,91,201],"is":[2,83,157],"often":[3],"noisy":[4],"and":[5,45,174,180,190,206],"incomplete.":[6],"Existing":[7],"completion":[8,43,53,120,202],"methods":[9,36,203],"usually":[10],"generate":[11],"the":[12,23,38,42,88,114,118,123,143,164,169,198],"complete":[13,147],"shapes":[14,121],"for":[15,50,75,99,146],"missing":[16],"regions":[17],"of":[18,41,117],"3D":[19,76],"objects":[20],"based":[21],"on":[22,185],"deterministic":[24],"learning":[25],"frameworks,":[26],"which":[27],"only":[28],"predict":[29],"a":[30,66,71,94,107,138,160],"single":[31,161],"reconstruction":[32,178],"output.":[33],"However,":[34],"these":[35],"ignore":[37],"ill-posed":[39],"nature":[40],"problem":[44],"do":[46],"not":[47],"fully":[48,131],"account":[49],"multiple":[51],"possible":[52],"predictions":[54],"corresponding":[55],"to":[56,86,112,130,141,167],"one":[57],"incomplete":[58],"input.":[59],"To":[60],"address":[61],"this":[62],"problem,":[63],"we":[64,105,136],"propose":[65,137],"flow-based":[67],"network":[68,156],"together":[69],"with":[70,150],"multi-modal":[72,124],"mapping":[73,145],"strategy":[74],"point":[77,90,200],"completion.":[79],"Specially,":[80],"an":[81],"encoder":[82],"first":[84],"introduced":[85],"encode":[87],"input":[89,173],"data":[92,192],"into":[93],"rich":[95],"latent":[96,125],"representation":[97],"suitable":[98],"conditioning":[100],"in":[101,128],"all":[102],"flow-layers.":[103],"Then":[104],"design":[106],"conditional":[108],"normalizing":[109],"flow":[110,155],"architecture":[111],"learn":[113],"exact":[115],"distribution":[116,170],"plausible":[119],"over":[122],"space.":[126],"Finally,":[127],"order":[129],"utilize":[132],"additional":[133],"shape":[134,148],"information,":[135],"tree-structured":[139],"decoder":[140],"perform":[142],"inverse":[144],"generation":[149],"high":[151],"fidelity.":[152],"The":[153],"proposed":[154],"trained":[158],"using":[159],"loss":[162,179],"named":[163],"negative":[165],"log-likelihood":[166],"capture":[168],"variations":[171],"between":[172],"output,":[175],"without":[176],"complex":[177],"adversarial":[181],"loss.":[182],"Extensive":[183],"experiments":[184],"ShapeNet":[186],"dataset,":[187],"KITTI":[188],"dataset":[189],"measured":[191],"demonstrate":[193],"that":[194],"our":[195],"method":[196],"outperforms":[197],"state-of-the-art":[199],"through":[204],"qualitative":[205],"quantitative":[207],"analysis.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2021-10-25T00:00:00"}
