{"id":"https://openalex.org/W7126056316","doi":"https://doi.org/10.1109/wpmc67460.2025.11351190","title":"Deep Learning-based Geometry Compression of Point Cloud Data","display_name":"Deep Learning-based Geometry Compression of Point Cloud Data","publication_year":2025,"publication_date":"2025-11-09","ids":{"openalex":"https://openalex.org/W7126056316","doi":"https://doi.org/10.1109/wpmc67460.2025.11351190"},"language":null,"primary_location":{"id":"doi:10.1109/wpmc67460.2025.11351190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wpmc67460.2025.11351190","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 28th International Symposium on Wireless Personal Multimedia Communications (WPMC)","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/A5124223668","display_name":"Mila Aldimirova","orcid":null},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":true,"raw_author_name":"Mila Aldimirova","raw_affiliation_strings":["Technical University of Sofia,Teleinfrastructure R &amp; D Lab,Sofia,Bulgaria"],"affiliations":[{"raw_affiliation_string":"Technical University of Sofia,Teleinfrastructure R &amp; D Lab,Sofia,Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016088751","display_name":"Radostina Petkova","orcid":"https://orcid.org/0000-0002-9731-4406"},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"Radostina Petkova","raw_affiliation_strings":["Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria"],"affiliations":[{"raw_affiliation_string":"Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049942182","display_name":"Ivaylo Bozhilov","orcid":"https://orcid.org/0009-0009-9166-9212"},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"Ivaylo Bozhilov","raw_affiliation_strings":["Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria"],"affiliations":[{"raw_affiliation_string":"Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005044211","display_name":"Krasimir Tonchev","orcid":"https://orcid.org/0000-0002-3332-666X"},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"Krasimir Tonchev","raw_affiliation_strings":["Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria"],"affiliations":[{"raw_affiliation_string":"Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054696693","display_name":"Agata Manolova","orcid":"https://orcid.org/0000-0002-8120-363X"},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"Agata Manolova","raw_affiliation_strings":["Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria"],"affiliations":[{"raw_affiliation_string":"Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055245125","display_name":"V. Poulkov","orcid":null},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"Vladimir Poulkov","raw_affiliation_strings":["Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria"],"affiliations":[{"raw_affiliation_string":"Technical University of Sofia,Faculty of Telecommunications,Sofia,Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5124223668"],"corresponding_institution_ids":["https://openalex.org/I31151848"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.70253485,"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":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9710000157356262,"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":0.9710000157356262,"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":0.008100000210106373,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.002400000113993883,"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/point-cloud","display_name":"Point cloud","score":0.8758999705314636},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6251000165939331},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.589900016784668},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5342000126838684},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5257999897003174},{"id":"https://openalex.org/keywords/compression-ratio","display_name":"Compression ratio","score":0.4146000146865845},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.3806000053882599},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.3702999949455261}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8758999705314636},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6251000165939331},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.589900016784668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5504000186920166},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5342000126838684},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5257999897003174},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.510200023651123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4927000105381012},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48579999804496765},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.4146000146865845},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.40059998631477356},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.3806000053882599},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3702999949455261},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C2776313386","wikidata":"https://www.wikidata.org/wiki/Q18018756","display_name":"Chamfer (geometry)","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.34119999408721924},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C136520226","wikidata":"https://www.wikidata.org/wiki/Q302814","display_name":"Geometric data analysis","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2985000014305115},{"id":"https://openalex.org/C141297171","wikidata":"https://www.wikidata.org/wiki/Q1143237","display_name":"Octree","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C187590223","wikidata":"https://www.wikidata.org/wiki/Q527628","display_name":"Holography","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.27480000257492065},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.2587999999523163}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wpmc67460.2025.11351190","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wpmc67460.2025.11351190","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 28th International Symposium on Wireless Personal Multimedia Communications (WPMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2152864241","https://openalex.org/W2796426482","https://openalex.org/W2905544027","https://openalex.org/W2922745530","https://openalex.org/W2963071695","https://openalex.org/W2964287951","https://openalex.org/W2982170926","https://openalex.org/W3014200484","https://openalex.org/W3106655268","https://openalex.org/W3131242954","https://openalex.org/W4214671570","https://openalex.org/W4311805949","https://openalex.org/W4403182632"],"related_works":[],"abstract_inverted_index":{"Point":[0],"clouds":[1],"have":[2],"found":[3],"widespread":[4],"application":[5],"in":[6],"computer":[7],"vision,":[8],"autonomous":[9],"driving,":[10],"augmented":[11],"and":[12,29,63,75,89],"virtual":[13],"reality,":[14],"holographic":[15],"telepresence,":[16],"etc.":[17],"Efficient":[18],"compression":[19,27,80,92],"of":[20],"3D":[21,49,129],"point":[22,50,78,130],"clouds,":[23],"achieving":[24,112],"both":[25,87],"high":[26],"ratios":[28],"minimal":[30],"loss,":[31],"is":[32,56,124],"essential":[33],"for":[34,48,72,79,128],"effective":[35,126],"data":[36],"transmission.":[37],"In":[38],"this":[39],"paper,":[40],"we":[41],"present":[42],"a":[43],"novel":[44],"deep":[45,90],"learning-based":[46],"autoencoder":[47],"cloud":[51,131],"geometry":[52],"compression.":[53,132],"The":[54,97],"model":[55,123],"trained":[57],"by":[58],"minimizing":[59],"the":[60],"Chamfer":[61],"Distance":[62],"evaluated":[64],"using":[65],"MPEG-standardized":[66],"metrics:":[67],"D1-Peak":[68],"Signal-to-Noise":[69],"Ratio":[70],"(D1-PSNR)":[71],"geometric":[73,102],"fidelity":[74],"bits":[76],"per":[77],"efficiency.":[81],"We":[82],"benchmark":[83],"our":[84,122],"approach":[85],"against":[86],"traditional":[88],"learning\u2013based":[91],"methods":[93],"on":[94],"two":[95],"datasets.":[96],"proposed":[98],"network":[99],"reconstructs":[100],"fine":[101],"details":[103],"more":[104],"accurately":[105],"than":[106],"FoldingNet":[107],"at":[108],"low":[109],"bitrates,":[110],"while":[111],"qualitative":[113],"results":[114],"comparable":[115],"to":[116],"Draco.":[117],"These":[118],"findings":[119],"demonstrate":[120],"that":[121],"an":[125],"solution":[127]},"counts_by_year":[],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2026-01-30T00:00:00"}
