{"id":"https://openalex.org/W4400034738","doi":"https://doi.org/10.1109/pcs60826.2024.10566435","title":"BMT-PCGC: Point Cloud Geometry Compression with Bidirectional Mask Transformer Entropy Model","display_name":"BMT-PCGC: Point Cloud Geometry Compression with Bidirectional Mask Transformer Entropy Model","publication_year":2024,"publication_date":"2024-06-12","ids":{"openalex":"https://openalex.org/W4400034738","doi":"https://doi.org/10.1109/pcs60826.2024.10566435"},"language":"en","primary_location":{"id":"doi:10.1109/pcs60826.2024.10566435","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/pcs60826.2024.10566435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Picture Coding Symposium (PCS)","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/A5072408542","display_name":"Monyneath Yim","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Monyneath Yim","raw_affiliation_strings":["National Chung Cheng University,Department of Electrical Engineering,Taiwan","Department of Electrical Engineering, National Chung Cheng University, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Chung Cheng University,Department of Electrical Engineering,Taiwan","institution_ids":["https://openalex.org/I148099254"]},{"raw_affiliation_string":"Department of Electrical Engineering, National Chung Cheng University, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104335940","display_name":"Bing-Han Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Bing-Han Wu","raw_affiliation_strings":["National Chung Cheng University,Department of Electrical Engineering,Taiwan","Department of Electrical Engineering, National Chung Cheng University, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Chung Cheng University,Department of Electrical Engineering,Taiwan","institution_ids":["https://openalex.org/I148099254"]},{"raw_affiliation_string":"Department of Electrical Engineering, National Chung Cheng University, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018255070","display_name":"Jui\u2010Chiu Chiang","orcid":"https://orcid.org/0000-0003-1397-8393"},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jui-Chiu Chiang","raw_affiliation_strings":["National Chung Cheng University,Department of Electrical Engineering,Taiwan","Department of Electrical Engineering, National Chung Cheng University, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Chung Cheng University,Department of Electrical Engineering,Taiwan","institution_ids":["https://openalex.org/I148099254"]},{"raw_affiliation_string":"Department of Electrical Engineering, National Chung Cheng University, Taiwan","institution_ids":["https://openalex.org/I148099254"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5072408542"],"corresponding_institution_ids":["https://openalex.org/I148099254"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08670686,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9991999864578247,"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/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/T11583","display_name":"Advanced Measurement and Metrology Techniques","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/point-cloud","display_name":"Point cloud","score":0.5906127095222473},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5359929800033569},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4989626407623291},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4681829512119293},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.367845356464386},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.23278754949569702},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.16634613275527954},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15452507138252258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.13591820001602173},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12833061814308167},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.06651458144187927}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5906127095222473},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5359929800033569},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4989626407623291},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4681829512119293},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.367845356464386},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.23278754949569702},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.16634613275527954},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15452507138252258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.13591820001602173},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12833061814308167},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.06651458144187927},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pcs60826.2024.10566435","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/pcs60826.2024.10566435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Picture Coding Symposium (PCS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.5299999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2594519801","https://openalex.org/W2785562966","https://openalex.org/W2949361041","https://openalex.org/W2964098744","https://openalex.org/W2976304245","https://openalex.org/W3113844551","https://openalex.org/W3159975835","https://openalex.org/W3195128047","https://openalex.org/W4221156617","https://openalex.org/W4226355936","https://openalex.org/W4297330752","https://openalex.org/W4310591442","https://openalex.org/W4311805949","https://openalex.org/W4316660344","https://openalex.org/W4372283849","https://openalex.org/W4385245566","https://openalex.org/W4386075996","https://openalex.org/W4390874546","https://openalex.org/W6739901393","https://openalex.org/W6754634825","https://openalex.org/W6810067190"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3016928466","https://openalex.org/W4389574804","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Point":[0],"cloud":[1,75,110],"compression":[2,29],"plays":[3],"a":[4,66,102],"critical":[5],"role":[6],"in":[7,38,44,82,127,153],"efficiently":[8],"handling":[9],"large":[10,39],"3D":[11],"datasets,":[12],"enabling":[13],"their":[14],"practical":[15],"usage.":[16],"An":[17],"accurate":[18],"entropy":[19,33,70],"model":[20,71],"is":[21],"essential":[22],"for":[23,73,97],"learned":[24],"codecs":[25],"to":[26,101,134],"achieve":[27],"good":[28],"performance.":[30],"Although":[31],"autoregressive":[32,104],"models":[34],"can":[35],"explore":[36],"dependencies":[37],"contexts,":[40],"they":[41],"are":[42],"inefficient":[43],"terms":[45,128,154],"of":[46,123,129,149,155],"complexity":[47],"and":[48,114,125,141,151],"may":[49],"miss":[50],"information":[51],"from":[52],"the":[53,83],"inverse":[54],"direction.":[55],"To":[56],"improve":[57],"coding":[58,111],"efficiency":[59],"while":[60],"guaranteeing":[61],"fast":[62],"decoding,":[63],"we":[64],"propose":[65],"bidirectional":[67,80],"mask":[68,84,88],"Transformer":[69],"(BMTEM)":[72],"point":[74,109],"geometry":[76],"compression,":[77],"by":[78],"leveraging":[79],"self-attention":[81],"Transformer.":[85],"The":[86],"pre-defined":[87],"schedules":[89],"facilitate":[90],"group-wise":[91],"autoregression,":[92],"which":[93],"improves":[94],"parallel":[95],"computation":[96],"faster":[98],"inference":[99],"compared":[100,133],"fully":[103],"approach.":[105],"Comparative":[106],"evaluations":[107],"against":[108],"standards":[112],"G-PCC":[113],"V-PCC":[115],"reveal":[116],"that":[117],"BMTEM":[118],"achieves":[119],"significant":[120],"bitrate":[121,147],"savings":[122],"53.22%":[124],"47.18%":[126],"D1-PSNR,":[130,156],"respectively.":[131,157],"When":[132],"other":[135],"deep":[136],"learning-based":[137],"methods":[138],"like":[139],"PCGCv2":[140],"ANFPCGC,":[142],"our":[143],"approach":[144],"demonstrates":[145],"average":[146],"reductions":[148],"20.01%":[150],"17.67%":[152]},"counts_by_year":[],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}