{"id":"https://openalex.org/W4416250094","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229396","title":"Self-Attention Based Multi-Scale Graph Auto-Encoder Network of 3D Meshes","display_name":"Self-Attention Based Multi-Scale Graph Auto-Encoder Network of 3D Meshes","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250094","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229396"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11229396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5071110323","display_name":"Saqib Nazir","orcid":"https://orcid.org/0000-0003-0098-1868"},"institutions":[{"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"]},{"id":"https://openalex.org/I98702875","display_name":"Universit\u00e9 de Caen Normandie","ror":"https://ror.org/051kpcy16","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210105918","https://openalex.org/I98702875"]},{"id":"https://openalex.org/I4210105918","display_name":"Normandie Universit\u00e9","ror":"https://ror.org/01k40cz91","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210105918"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Saqib Nazir","raw_affiliation_strings":["Université Caen Normandie, ENSICAEN, CNRS, Normandie Univ,Caen,France,F-14000"],"affiliations":[{"raw_affiliation_string":"Université Caen Normandie, ENSICAEN, CNRS, Normandie Univ,Caen,France,F-14000","institution_ids":["https://openalex.org/I98702875","https://openalex.org/I1294671590","https://openalex.org/I4210105918"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062753174","display_name":"Olivier L\u00e9zoray","orcid":"https://orcid.org/0000-0003-0540-543X"},"institutions":[{"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"]},{"id":"https://openalex.org/I4210105918","display_name":"Normandie Universit\u00e9","ror":"https://ror.org/01k40cz91","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210105918"]},{"id":"https://openalex.org/I98702875","display_name":"Universit\u00e9 de Caen Normandie","ror":"https://ror.org/051kpcy16","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210105918","https://openalex.org/I98702875"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Olivier L\u00e9zoray","raw_affiliation_strings":["Université Caen Normandie, ENSICAEN, CNRS, Normandie Univ,Caen,France,F-14000"],"affiliations":[{"raw_affiliation_string":"Université Caen Normandie, ENSICAEN, CNRS, Normandie Univ,Caen,France,F-14000","institution_ids":["https://openalex.org/I98702875","https://openalex.org/I1294671590","https://openalex.org/I4210105918"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114376778","display_name":"S\u00e9bastien Bougleux","orcid":"https://orcid.org/0000-0002-4581-7570"},"institutions":[{"id":"https://openalex.org/I4210105918","display_name":"Normandie Universit\u00e9","ror":"https://ror.org/01k40cz91","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210105918"]},{"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"]},{"id":"https://openalex.org/I98702875","display_name":"Universit\u00e9 de Caen Normandie","ror":"https://ror.org/051kpcy16","country_code":"FR","type":"education","lineage":["https://openalex.org/I4210105918","https://openalex.org/I98702875"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"S\u00e9bastien Bougleux","raw_affiliation_strings":["Université Caen Normandie, ENSICAEN, CNRS, Normandie Univ,Caen,France,F-14000"],"affiliations":[{"raw_affiliation_string":"Université Caen Normandie, ENSICAEN, CNRS, Normandie Univ,Caen,France,F-14000","institution_ids":["https://openalex.org/I98702875","https://openalex.org/I1294671590","https://openalex.org/I4210105918"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5071110323"],"corresponding_institution_ids":["https://openalex.org/I1294671590","https://openalex.org/I4210105918","https://openalex.org/I98702875"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37864439,"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":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9681000113487244,"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":0.9681000113487244,"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/T11448","display_name":"Face recognition and analysis","score":0.0044999998062849045,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.003000000026077032,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/polygon-mesh","display_name":"Polygon mesh","score":0.8766000270843506},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics","score":0.5008000135421753},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47350001335144043},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4659999907016754},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.4438000023365021},{"id":"https://openalex.org/keywords/geometric-data-analysis","display_name":"Geometric data analysis","score":0.4047999978065491},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.39809998869895935},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.34950000047683716},{"id":"https://openalex.org/keywords/geometric-networks","display_name":"Geometric networks","score":0.3474000096321106},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3395000100135803}],"concepts":[{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.8766000270843506},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7145000100135803},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.5008000135421753},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47350001335144043},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4659999907016754},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43059998750686646},{"id":"https://openalex.org/C136520226","wikidata":"https://www.wikidata.org/wiki/Q302814","display_name":"Geometric data analysis","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.39809998869895935},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3880000114440918},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38100001215934753},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.34950000047683716},{"id":"https://openalex.org/C49777392","wikidata":"https://www.wikidata.org/wiki/Q5535495","display_name":"Geometric networks","level":3,"score":0.3474000096321106},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C160403270","wikidata":"https://www.wikidata.org/wiki/Q7667943","display_name":"T-vertices","level":4,"score":0.3391000032424927},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3197999894618988},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.30790001153945923},{"id":"https://openalex.org/C181095308","wikidata":"https://www.wikidata.org/wiki/Q1541599","display_name":"Geometric primitive","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C53471067","wikidata":"https://www.wikidata.org/wiki/Q7574076","display_name":"Spatial network","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C2779521785","wikidata":"https://www.wikidata.org/wiki/Q5535529","display_name":"Geometry processing","level":3,"score":0.29490000009536743},{"id":"https://openalex.org/C141297171","wikidata":"https://www.wikidata.org/wiki/Q1143237","display_name":"Octree","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C42087268","wikidata":"https://www.wikidata.org/wiki/Q1886184","display_name":"Marching cubes","level":3,"score":0.28450000286102295},{"id":"https://openalex.org/C41365986","wikidata":"https://www.wikidata.org/wiki/Q104153293","display_name":"Level of detail","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C194401833","wikidata":"https://www.wikidata.org/wiki/Q3456889","display_name":"Triangle mesh","level":3,"score":0.27959999442100525},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.27160000801086426},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.2667999863624573},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.2621000111103058},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.26109999418258667},{"id":"https://openalex.org/C459310","wikidata":"https://www.wikidata.org/wiki/Q117801","display_name":"Computational science","level":1,"score":0.25859999656677246},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11229396","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229396","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1626653188","https://openalex.org/W1935685005","https://openalex.org/W2017107803","https://openalex.org/W2107037917","https://openalex.org/W2235901111","https://openalex.org/W2604524889","https://openalex.org/W2768683308","https://openalex.org/W2769666294","https://openalex.org/W2791092480","https://openalex.org/W2883221003","https://openalex.org/W2917887692","https://openalex.org/W2946733714","https://openalex.org/W2997233412","https://openalex.org/W3008956107","https://openalex.org/W3128223926","https://openalex.org/W3217293147","https://openalex.org/W4213188734","https://openalex.org/W4214549609","https://openalex.org/W4321020689","https://openalex.org/W4384471068","https://openalex.org/W4385489997","https://openalex.org/W4385490328","https://openalex.org/W4390873278","https://openalex.org/W4394625656","https://openalex.org/W4402753765"],"related_works":[],"abstract_inverted_index":{"3D":[0,33,85],"meshes":[1,34,117],"are":[2],"fundamental":[3],"data":[4,26],"representations":[5,120],"for":[6],"capturing":[7],"complex":[8],"geometric":[9,160],"shapes":[10],"in":[11,24,108,180],"computer":[12],"vision":[13],"and":[14,76,104,154,162],"graphics":[15],"applications.":[16],"While":[17],"Convolutional":[18,46],"Neural":[19],"Networks":[20,47],"(CNNs)":[21],"have":[22],"excelled":[23],"structured":[25],"like":[27,121],"images,":[28],"extending":[29],"them":[30],"to":[31,38,55,72,99],"irregular":[32],"is":[35],"challenging":[36],"due":[37],"the":[39,43,109,130,136,169,176],"non-Euclidean":[40],"nature":[41],"of":[42,178,182],"data.":[44],"Graph":[45],"(GCNs)":[48],"offer":[49],"a":[50,90,147],"solution":[51],"by":[52],"applying":[53],"convolutions":[54],"graph-structured":[56],"data,":[57],"but":[58],"many":[59],"existing":[60],"methods":[61],"rely":[62],"on":[63,168],"isotropic":[64],"filters":[65],"or":[66,124],"spectral":[67],"decomposition,":[68],"limiting":[69],"their":[70],"ability":[71],"capture":[73,157],"both":[74,102,158],"local":[75,105,155,164],"global":[77,103,153],"mesh":[78,133],"features.":[79],"In":[80],"this":[81],"paper,":[82],"we":[83],"introduce":[84],"Geometric":[86],"Mesh":[87],"Network":[88],"(3DGeoMeshNet),":[89],"novel":[91],"GCN-based":[92],"framework":[93],"that":[94,115],"uses":[95],"anisotropic":[96],"convolution":[97],"layers":[98],"effectively":[100],"learn":[101],"features":[106,146],"directly":[107],"spatial":[110],"domain.":[111],"Unlike":[112],"previous":[113],"approaches":[114],"convert":[116],"into":[118],"intermediate":[119],"voxel":[122],"grids":[123],"point":[125],"clouds,":[126],"our":[127],"method":[128],"preserves":[129],"original":[131],"polygonal":[132],"format":[134],"throughout":[135],"reconstruction":[137,183],"process,":[138],"enabling":[139],"more":[140],"accurate":[141],"shape":[142],"reconstruction.":[143],"Our":[144],"architecture":[145],"multi-scale":[148],"encoder-decoder":[149],"structure,":[150],"where":[151],"separate":[152],"pathways":[156],"large-scale":[159],"structures":[161],"fine-grained":[163],"details.":[165],"Extensive":[166],"experiments":[167],"COMA":[170],"dataset":[171],"containing":[172],"human":[173],"faces":[174],"demonstrate":[175],"efficiency":[177],"3DGeoMeshNet":[179],"terms":[181],"accuracy.":[184]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}