{"id":"https://openalex.org/W4408354316","doi":"https://doi.org/10.1109/icassp49660.2025.10889736","title":"Full-Reference Point Cloud Quality Assessment with Multimodal Large Language Models","display_name":"Full-Reference Point Cloud Quality Assessment with Multimodal Large Language Models","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408354316","doi":"https://doi.org/10.1109/icassp49660.2025.10889736"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10889736","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889736","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/A5060700521","display_name":"Ryosuke Watanabe","orcid":"https://orcid.org/0000-0002-0720-7763"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryosuke Watanabe","raw_affiliation_strings":["KDDI Research, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI Research, Inc","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102945601","display_name":"Tomoaki Konno","orcid":"https://orcid.org/0000-0003-3110-6580"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoaki Konno","raw_affiliation_strings":["KDDI Research, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI Research, Inc","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103839794","display_name":"Hiroshi Sankoh","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Sankoh","raw_affiliation_strings":["KDDI Research, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI Research, Inc","institution_ids":["https://openalex.org/I4210164495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009758620","display_name":"Bryan Tanaka","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bryan Tanaka","raw_affiliation_strings":["Google, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google, Inc","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032438911","display_name":"Tatsuya Kobayashi","orcid":"https://orcid.org/0000-0002-2869-6148"},"institutions":[{"id":"https://openalex.org/I4210164495","display_name":"KDDI Research (Japan)","ror":"https://ror.org/05qsqt662","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210164495"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tatsuya Kobayashi","raw_affiliation_strings":["KDDI Research, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KDDI Research, Inc","institution_ids":["https://openalex.org/I4210164495"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9845,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.68947953,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"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":0.9668999910354614,"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":0.9668999910354614,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9495999813079834,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7775396108627319},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6391443610191345},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.535443127155304},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.481361448764801},{"id":"https://openalex.org/keywords/quality-assessment","display_name":"Quality assessment","score":0.44652605056762695},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4421542286872864},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3887197971343994},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32525867223739624},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.16716909408569336},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.09778690338134766},{"id":"https://openalex.org/keywords/evaluation-methods","display_name":"Evaluation methods","score":0.08968690037727356},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07677456736564636},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06060230731964111}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7775396108627319},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6391443610191345},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.535443127155304},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.481361448764801},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.44652605056762695},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4421542286872864},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3887197971343994},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32525867223739624},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.16716909408569336},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09778690338134766},{"id":"https://openalex.org/C3018395757","wikidata":"https://www.wikidata.org/wiki/Q1379672","display_name":"Evaluation methods","level":2,"score":0.08968690037727356},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07677456736564636},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06060230731964111},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10889736","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889736","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":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335839","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1580389772","https://openalex.org/W2133665775","https://openalex.org/W2793293836","https://openalex.org/W2905544027","https://openalex.org/W2970302264","https://openalex.org/W2970641574","https://openalex.org/W3015751022","https://openalex.org/W3032119513","https://openalex.org/W3035130434","https://openalex.org/W3046961466","https://openalex.org/W3094394107","https://openalex.org/W3148420801","https://openalex.org/W3174069367","https://openalex.org/W3176345994","https://openalex.org/W3183144290","https://openalex.org/W3186878598","https://openalex.org/W3190212754","https://openalex.org/W3207150002","https://openalex.org/W4282928804","https://openalex.org/W4288084829","https://openalex.org/W4297330272","https://openalex.org/W4313318661","https://openalex.org/W4320040053","https://openalex.org/W4372346078","https://openalex.org/W4383220231","https://openalex.org/W4388711634","https://openalex.org/W4389230952","https://openalex.org/W4389250084","https://openalex.org/W4389474382","https://openalex.org/W4392908985","https://openalex.org/W4399793749","https://openalex.org/W4402727764","https://openalex.org/W4402916700","https://openalex.org/W4403791553","https://openalex.org/W4404536559","https://openalex.org/W6683984541","https://openalex.org/W6739483711","https://openalex.org/W6796581206","https://openalex.org/W6855618270","https://openalex.org/W6859870462"],"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":{"Point":[0,16],"cloud":[1,59],"quality":[2,76,82],"frequently":[3],"degrades":[4],"during":[5],"various":[6],"processes,":[7],"such":[8],"as":[9],"scanning,":[10],"compression,":[11],"and":[12,26,79,114,130],"transmission.":[13],"Hence,":[14],"reliable":[15],"Cloud":[17],"Quality":[18],"Assessment":[19],"(PCQA)":[20],"methods":[21],"are":[22],"essential":[23],"for":[24],"detecting":[25],"mitigating":[27],"the":[28,107,139],"degradation":[29],"in":[30],"3D":[31],"applications.":[32],"This":[33],"paper":[34],"proposes":[35],"an":[36],"accurate":[37],"full-reference":[38],"PCQA":[39,65,94],"method":[40,50],"that":[41,106],"leverages":[42],"Multimodal":[43],"Large":[44],"Language":[45],"Models":[46],"(MLLMs).":[47],"The":[48],"proposed":[49],"utilizes":[51],"responses":[52],"generated":[53],"by":[54,124],"MLLMs":[55],"to":[56,100,128,134,138],"assess":[57],"point":[58],"quality.":[60],"We":[61],"introduce":[62],"three":[63,121],"innovative":[64],"metrics":[66,95],"derived":[67],"from":[68],"MLLMs:":[69],"1)":[70],"response":[71,77,83],"similarity":[72],"score,":[73,78],"2)":[74],"relative":[75],"3)":[80],"absolute":[81],"score.":[84],"In":[85],"addition,":[86],"we":[87],"integrate":[88],"these":[89],"MLLM-based":[90],"scores":[91],"with":[92],"conventional":[93],"using":[96],"support":[97],"vector":[98],"regression":[99],"improve":[101],"accuracy.":[102],"Experimental":[103],"results":[104],"demonstrate":[105],"average":[108],"Pearson\u2019s":[109],"Linear":[110],"Correlation":[111,117],"Coefficient":[112,118],"(PLCC)":[113],"Spearman\u2019s":[115],"Rank-Order":[116],"(SROCC)":[119],"across":[120],"datasets":[122],"improved":[123],"0.046":[125],"(from":[126,132],"0.871":[127],"0.917)":[129],"0.055":[131],"0.842":[133],"0.897),":[135],"respectively,":[136],"compared":[137],"state-of-the-art":[140],"FR-PCQA":[141],"method.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
