{"id":"https://openalex.org/W4415818001","doi":"https://doi.org/10.3390/jimaging11110387","title":"GATF-PCQA: A Graph Attention Transformer Fusion Network for Point Cloud Quality Assessment","display_name":"GATF-PCQA: A Graph Attention Transformer Fusion Network for Point Cloud Quality Assessment","publication_year":2025,"publication_date":"2025-11-01","ids":{"openalex":"https://openalex.org/W4415818001","doi":"https://doi.org/10.3390/jimaging11110387","pmid":"https://pubmed.ncbi.nlm.nih.gov/41295104"},"language":"en","primary_location":{"id":"doi:10.3390/jimaging11110387","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging11110387","pdf_url":null,"source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/jimaging11110387","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072080483","display_name":"Abdelouahed Laazoufi","orcid":"https://orcid.org/0009-0006-1157-5717"},"institutions":[{"id":"https://openalex.org/I126477371","display_name":"Mohammed V University","ror":"https://ror.org/00r8w8f84","country_code":"MA","type":"education","lineage":["https://openalex.org/I126477371"]}],"countries":["MA"],"is_corresponding":true,"raw_author_name":"Abdelouahed Laazoufi","raw_affiliation_strings":["Research Laboratory in Computer Science and Telecommunications (LRIT), Faculty of Sciences, Mohammed V University in Rabat, Rabat 1014, Morocco"],"affiliations":[{"raw_affiliation_string":"Research Laboratory in Computer Science and Telecommunications (LRIT), Faculty of Sciences, Mohammed V University in Rabat, Rabat 1014, Morocco","institution_ids":["https://openalex.org/I126477371"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046609840","display_name":"Mohammed El Hassouni","orcid":"https://orcid.org/0000-0002-6741-4799"},"institutions":[{"id":"https://openalex.org/I126477371","display_name":"Mohammed V University","ror":"https://ror.org/00r8w8f84","country_code":"MA","type":"education","lineage":["https://openalex.org/I126477371"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Mohammed El Hassouni","raw_affiliation_strings":["Faculty of Letters and Human Sciences in Rabat, Mohammed V University in Rabat, Rabat 8007, Morocco"],"affiliations":[{"raw_affiliation_string":"Faculty of Letters and Human Sciences in Rabat, Mohammed V University in Rabat, Rabat 8007, Morocco","institution_ids":["https://openalex.org/I126477371"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006125158","display_name":"Hocine Cherifi","orcid":"https://orcid.org/0000-0001-9124-4921"},"institutions":[{"id":"https://openalex.org/I177064439","display_name":"Universit\u00e9 de Bourgogne","ror":"https://ror.org/03k1bsr36","country_code":"FR","type":"education","lineage":["https://openalex.org/I177064439"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Hocine Cherifi","raw_affiliation_strings":["Carnot Interdisciplinary Laboratory of Burgundy (ICB) UMR 6303 CNRS, University of Burgundy, 21000 Dijon, France"],"affiliations":[{"raw_affiliation_string":"Carnot Interdisciplinary Laboratory of Burgundy (ICB) UMR 6303 CNRS, University of Burgundy, 21000 Dijon, France","institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I177064439"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5006125158","https://openalex.org/A5072080483"],"corresponding_institution_ids":["https://openalex.org/I126477371","https://openalex.org/I1294671590","https://openalex.org/I177064439"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.35915807,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":"11","first_page":"387","last_page":"387"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.911899983882904,"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":0.911899983882904,"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":0.00860000029206276,"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"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.007199999876320362,"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":0.7268999814987183},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5392000079154968},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5228000283241272},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4918999969959259},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.48890000581741333},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.47920000553131104},{"id":"https://openalex.org/keywords/adjacency-list","display_name":"Adjacency list","score":0.45739999413490295},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4413999915122986},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.42590001225471497},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3718000054359436}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8241000175476074},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7268999814987183},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5392000079154968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5235000252723694},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5228000283241272},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4918999969959259},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.48890000581741333},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.47920000553131104},{"id":"https://openalex.org/C110484373","wikidata":"https://www.wikidata.org/wiki/Q264398","display_name":"Adjacency list","level":2,"score":0.45739999413490295},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4413999915122986},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.42590001225471497},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3919000029563904},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3718000054359436},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.36000001430511475},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3589000105857849},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.3547999858856201},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3321000039577484},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3190999925136566},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.30730000138282776},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30660000443458557},{"id":"https://openalex.org/C106937863","wikidata":"https://www.wikidata.org/wiki/Q7236518","display_name":"Power graph analysis","level":3,"score":0.2964000105857849},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2838999927043915},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C112953755","wikidata":"https://www.wikidata.org/wiki/Q739462","display_name":"Graph drawing","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2676999866962433}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/jimaging11110387","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging11110387","pdf_url":null,"source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging","raw_type":"journal-article"},{"id":"pmid:41295104","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41295104","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of imaging","raw_type":null},{"id":"pmh:oai:doaj.org/article:8f0d17513542491f8020a19d9d53851f","is_oa":true,"landing_page_url":"https://doaj.org/article/8f0d17513542491f8020a19d9d53851f","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Imaging, Vol 11, Iss 11, p 387 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/jimaging11110387","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging11110387","pdf_url":null,"source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1977725648","https://openalex.org/W1982471090","https://openalex.org/W2046119925","https://openalex.org/W2067191022","https://openalex.org/W2071965987","https://openalex.org/W2114582993","https://openalex.org/W2133665775","https://openalex.org/W2469033579","https://openalex.org/W2789257827","https://openalex.org/W2793293836","https://openalex.org/W2793379982","https://openalex.org/W2890403598","https://openalex.org/W2893723229","https://openalex.org/W2954893658","https://openalex.org/W2963509914","https://openalex.org/W2967864465","https://openalex.org/W2979750740","https://openalex.org/W2980780662","https://openalex.org/W2996855898","https://openalex.org/W2998456637","https://openalex.org/W3011477772","https://openalex.org/W3013177219","https://openalex.org/W3015751022","https://openalex.org/W3016718200","https://openalex.org/W3032119513","https://openalex.org/W3035130434","https://openalex.org/W3037320139","https://openalex.org/W3089343273","https://openalex.org/W3089703561","https://openalex.org/W3090476588","https://openalex.org/W3094394107","https://openalex.org/W3109895324","https://openalex.org/W3115362998","https://openalex.org/W3172390543","https://openalex.org/W3174069367","https://openalex.org/W3183144290","https://openalex.org/W3190212754","https://openalex.org/W3200938421","https://openalex.org/W3202211958","https://openalex.org/W3207498402","https://openalex.org/W3211374646","https://openalex.org/W4200634525","https://openalex.org/W4221128793","https://openalex.org/W4282813785","https://openalex.org/W4285266685","https://openalex.org/W4294982727","https://openalex.org/W4304758157","https://openalex.org/W4308211562","https://openalex.org/W4308235789","https://openalex.org/W4313534839","https://openalex.org/W4323519265","https://openalex.org/W4362480394","https://openalex.org/W4372260179","https://openalex.org/W4382407310","https://openalex.org/W4385768180","https://openalex.org/W4390284837","https://openalex.org/W4391448717","https://openalex.org/W4396834481","https://openalex.org/W4402727313","https://openalex.org/W4402979567","https://openalex.org/W4408163772","https://openalex.org/W4411301135","https://openalex.org/W4411870868","https://openalex.org/W4413359419","https://openalex.org/W4414712795"],"related_works":[],"abstract_inverted_index":{"Point":[0],"cloud":[1,82],"quality":[2,141,179],"assessment":[3],"remains":[4],"a":[5,36,76,101,106,124,129,139],"critical":[6],"challenge":[7],"due":[8],"to":[9,24,68],"the":[10,22,80,117,135,175],"high":[11,162],"dimensionality":[12],"and":[13,64,72,93,122,153],"irregular":[14],"structure":[15],"of":[16,53,79,119,178],"3D":[17],"data,":[18],"as":[19,21],"well":[20],"need":[23],"align":[25],"objective":[26],"predictions":[27],"with":[28,45,164],"human":[29,165],"perception.":[30],"To":[31],"solve":[32],"this,":[33],"we":[34],"suggest":[35],"novel":[37,107],"graph-based":[38,77],"learning":[39],"architecture":[40],"that":[41,158],"integrates":[42],"perceptual":[43,59,91,176],"features":[44,121,137],"advanced":[46],"graph":[47],"neural":[48],"networks.":[49],"Our":[50],"method":[51,160],"consists":[52],"four":[54],"main":[55],"stages:":[56],"First,":[57],"key":[58],"features,":[60],"including":[61],"curvature,":[62],"saliency,":[63],"color,":[65],"are":[66],"extracted":[67],"capture":[69],"relevant":[70],"geometric":[71],"visual":[73],"distortions.":[74],"Second,":[75],"representation":[78],"point":[81],"is":[83],"created":[84],"using":[85],"these":[86,120],"characteristics,":[87],"where":[88],"nodes":[89],"represent":[90],"clusters":[92],"weighted":[94],"edges":[95],"encode":[96],"their":[97],"feature":[98],"similarities,":[99],"yielding":[100],"structured":[102],"adjacency":[103],"matrix.":[104],"Third,":[105],"Graph":[108,130],"Attention":[109],"Network":[110,132],"Transformer":[111],"Fusion":[112],"(GATF)":[113],"module":[114],"dynamically":[115],"refines":[116],"importance":[118],"generates":[123],"unified,":[125],"view-specific":[126],"representation.":[127],"Finally,":[128],"Convolutional":[131],"(GCN)":[133],"regresses":[134],"fused":[136],"into":[138],"final":[140],"score.":[142],"We":[143],"validate":[144],"our":[145,159],"approach":[146],"on":[147],"three":[148],"benchmark":[149],"datasets:":[150],"ICIP2020,":[151],"WPC,":[152],"SJTU-PCQA.":[154],"Experimental":[155],"results":[156],"demonstrate":[157],"achieves":[161],"correlation":[163],"subjective":[166],"scores,":[167],"outperforming":[168],"existing":[169],"state-of-the-art":[170],"metrics":[171],"by":[172],"effectively":[173],"modeling":[174],"mechanisms":[177],"judgment.":[180]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-03T00:00:00"}