{"id":"https://openalex.org/W4408352457","doi":"https://doi.org/10.1109/icassp49660.2025.10888353","title":"Multi-modal Dynamic Point Cloud Geometric Compression Based on Bidirectional Recurrent Scene Flow*","display_name":"Multi-modal Dynamic Point Cloud Geometric Compression Based on Bidirectional Recurrent Scene Flow*","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408352457","doi":"https://doi.org/10.1109/icassp49660.2025.10888353"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10888353","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888353","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5077654954","display_name":"Fangzhe Nan","orcid":null},"institutions":[{"id":"https://openalex.org/I75059550","display_name":"Zhejiang Gongshang University","ror":"https://ror.org/0569mkk41","country_code":"CN","type":"education","lineage":["https://openalex.org/I75059550"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fangzhe Nan","raw_affiliation_strings":["Zhejiang Gongshang University,School of Statistics and Mathematics"],"affiliations":[{"raw_affiliation_string":"Zhejiang Gongshang University,School of Statistics and Mathematics","institution_ids":["https://openalex.org/I75059550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079905341","display_name":"Frederick W. B. Li","orcid":"https://orcid.org/0000-0002-4283-4228"},"institutions":[{"id":"https://openalex.org/I190082696","display_name":"Durham University","ror":"https://ror.org/01v29qb04","country_code":"GB","type":"education","lineage":["https://openalex.org/I190082696"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Frederick Li","raw_affiliation_strings":["University of Durham"],"affiliations":[{"raw_affiliation_string":"University of Durham","institution_ids":["https://openalex.org/I190082696"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005636812","display_name":"Zhuoyue Wang","orcid":"https://orcid.org/0009-0000-4350-5584"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhuoyue Wang","raw_affiliation_strings":["University of California,Berkeley"],"affiliations":[{"raw_affiliation_string":"University of California,Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003981917","display_name":"Gary K.L. Tam","orcid":"https://orcid.org/0000-0001-7387-5180"},"institutions":[{"id":"https://openalex.org/I39586589","display_name":"Swansea University","ror":"https://ror.org/053fq8t95","country_code":"GB","type":"education","lineage":["https://openalex.org/I39586589"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gary K.L. Tam","raw_affiliation_strings":["Swansea University"],"affiliations":[{"raw_affiliation_string":"Swansea University","institution_ids":["https://openalex.org/I39586589"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103240302","display_name":"Zhaoyi Jiang","orcid":"https://orcid.org/0000-0001-5347-7935"},"institutions":[{"id":"https://openalex.org/I75059550","display_name":"Zhejiang Gongshang University","ror":"https://ror.org/0569mkk41","country_code":"CN","type":"education","lineage":["https://openalex.org/I75059550"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoyi Jiang","raw_affiliation_strings":["Zhejiang Gongshang University,School of Computer Science and Technolgy"],"affiliations":[{"raw_affiliation_string":"Zhejiang Gongshang University,School of Computer Science and Technolgy","institution_ids":["https://openalex.org/I75059550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116594339","display_name":"DongZheng DongZheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210102840","display_name":"Ubiquitous Energy (United States)","ror":"https://ror.org/01b06j989","country_code":"US","type":"company","lineage":["https://openalex.org/I4210102840"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"DongZheng DongZheng","raw_affiliation_strings":["Universal Ubiquitous Technology Co., LTD"],"affiliations":[{"raw_affiliation_string":"Universal Ubiquitous Technology Co., LTD","institution_ids":["https://openalex.org/I4210102840"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015699943","display_name":"Bailin Yang","orcid":"https://orcid.org/0000-0003-1754-5595"},"institutions":[{"id":"https://openalex.org/I75059550","display_name":"Zhejiang Gongshang University","ror":"https://ror.org/0569mkk41","country_code":"CN","type":"education","lineage":["https://openalex.org/I75059550"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bailin Yang","raw_affiliation_strings":["Zhejiang Gongshang University,School of Computer Science and Technolgy"],"affiliations":[{"raw_affiliation_string":"Zhejiang Gongshang University,School of Computer Science and Technolgy","institution_ids":["https://openalex.org/I75059550"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5077654954"],"corresponding_institution_ids":["https://openalex.org/I75059550"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06342602,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9984999895095825,"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":0.9984999895095825,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9943000078201294,"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/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.9922000169754028,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7382030487060547},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7281720042228699},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.7079663276672363},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.5400586128234863},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.5132381916046143},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.48665982484817505},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4337303638458252},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.11250588297843933},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10252085328102112},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07266679406166077}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7382030487060547},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7281720042228699},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7079663276672363},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.5400586128234863},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.5132381916046143},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.48665982484817505},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4337303638458252},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.11250588297843933},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10252085328102112},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07266679406166077},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10888353","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888353","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320006","display_name":"Royal Society","ror":"https://ror.org/03wnrjx87"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1498318113","https://openalex.org/W2319503556","https://openalex.org/W2905544027","https://openalex.org/W2963231572","https://openalex.org/W3014200484","https://openalex.org/W3016258792","https://openalex.org/W3025708905","https://openalex.org/W3159975835","https://openalex.org/W3170030651","https://openalex.org/W3179630053","https://openalex.org/W3196733449","https://openalex.org/W3203898101","https://openalex.org/W4221156617","https://openalex.org/W4225144468","https://openalex.org/W4366601947","https://openalex.org/W4375869241","https://openalex.org/W4378191150","https://openalex.org/W4386701089","https://openalex.org/W4387968031","https://openalex.org/W4390534472","https://openalex.org/W4390873363","https://openalex.org/W4393156166","https://openalex.org/W4403809023","https://openalex.org/W6843220554"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W3150465815","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W1997222214","https://openalex.org/W2560439919","https://openalex.org/W4389340727","https://openalex.org/W2802581102","https://openalex.org/W4205786897"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"methods":[2,42,51],"have":[3,43],"recently":[4],"shown":[5],"significant":[6],"promise":[7],"in":[8,26,136,162],"compressing":[9],"the":[10,131,189,221],"geometric":[11],"features":[12,172],"of":[13,133,191,207,223],"point":[14,21,39,84,109,137,170,232],"clouds.":[15],"However,":[16],"challenges":[17],"arise":[18],"when":[19],"consecutive":[20],"clouds":[22,138],"contain":[23],"holes,":[24],"resulting":[25],"incomplete":[27],"information":[28,126,142],"that":[29],"complicates":[30],"motion":[31,59,153,160,175],"estimation.":[32],"To":[33,76],"our":[34,192],"knowledge,":[35],"most":[36],"existing":[37,196],"dynamic":[38,83,231],"cloud":[40,85,110,171,233],"compression":[41,74,86],"largely":[44],"overlooked":[45],"this":[46],"critical":[47],"issue.":[48],"Moreover,":[49],"these":[50,78],"typically":[52],"employ":[53],"a":[54,82,117,148],"multi-scale":[55,149],"single-pass":[56],"approach":[57,123],"for":[58,94,230],"estimation,":[60],"performing":[61],"only":[62],"one":[63],"estimation":[64,154,176],"at":[65],"each":[66],"scale.":[67],"This":[68,129,156],"limits":[69],"accuracy":[70],"and":[71,111,165,173,186,214,227],"adversely":[72],"impacts":[73],"performance.":[75],"address":[77],"challenges,":[79],"we":[80,106,146],"propose":[81],"model":[87],"called":[88],"M2BR-DPCC":[89,198],"(Multi-Modal":[90],"Multi-Scale":[91],"Bidirectional":[92],"Recursion":[93],"Dynamic":[95],"Point":[96],"Cloud":[97],"Compression).":[98],"Our":[99],"method":[100],"introduces":[101],"two":[102],"key":[103],"innovations.":[104],"First,":[105],"integrate":[107],"both":[108,163],"image":[112],"data":[113,135,226],"as":[114],"inputs,":[115],"leveraging":[116,224],"multi-modal":[118,225],"feature":[119],"representation":[120],"completion":[121],"(MFRepC)":[122],"to":[124,195],"align":[125],"across":[127],"modalities.":[128],"addresses":[130],"issue":[132],"missing":[134],"by":[139],"using":[140],"complementary":[141],"from":[143],"images.":[144],"Second,":[145],"implement":[147],"bidirectional":[150,228],"recursive":[151],"(MSBR)":[152],"method.":[155],"module":[157],"iteratively":[158],"refines":[159],"flows":[161],"forward":[164],"backward":[166],"directions,":[167],"progressively":[168],"enhancing":[169],"improving":[174],"accuracy.":[177],"Experimental":[178],"results":[179,219],"on":[180],"widely":[181],"used":[182],"datasets,":[183],"including":[184],"MVUB":[185],"8iVFB,":[187],"demonstrate":[188],"effectiveness":[190],"approach.":[193],"Compared":[194],"methods,":[197],"achieves":[199],"superior":[200],"performance,":[201],"with":[202],"an":[203],"average":[204],"BD-rate":[205],"improvement":[206],"95.23%":[208],"over":[209,212,216],"V-PCC,":[210],"12.92%":[211],"D-DPCC,":[213],"16.16%":[215],"patchDPCC.":[217],"These":[218],"underscore":[220],"potential":[222],"refinement":[229],"compression.":[234]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}