{"id":"https://openalex.org/W4406859144","doi":"https://doi.org/10.1109/vcip63160.2024.10849821","title":"Compressing 3D Gaussian Splatting via a Generalizable Neural Coder","display_name":"Compressing 3D Gaussian Splatting via a Generalizable Neural Coder","publication_year":2024,"publication_date":"2024-12-08","ids":{"openalex":"https://openalex.org/W4406859144","doi":"https://doi.org/10.1109/vcip63160.2024.10849821"},"language":"en","primary_location":{"id":"doi:10.1109/vcip63160.2024.10849821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip63160.2024.10849821","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Visual Communications and Image Processing (VCIP)","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/A5016588601","display_name":"Junteng Zhang","orcid":"https://orcid.org/0000-0002-8204-4343"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junteng Zhang","raw_affiliation_strings":["Nanjing University,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University,Nanjing,China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103246081","display_name":"Tong Chen","orcid":"https://orcid.org/0000-0001-5020-6099"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Chen","raw_affiliation_strings":["Nanjing University,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University,Nanjing,China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058268359","display_name":"Hao Zhu","orcid":"https://orcid.org/0000-0003-4411-0933"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhu","raw_affiliation_strings":["Nanjing University,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University,Nanjing,China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100391493","display_name":"Dong Wang","orcid":"https://orcid.org/0000-0002-6976-4004"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dong Wang","raw_affiliation_strings":["OPPO Inc.,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"OPPO Inc.,Nanjing,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028059517","display_name":"Dandan Ding","orcid":"https://orcid.org/0000-0003-2911-1321"},"institutions":[{"id":"https://openalex.org/I163151501","display_name":"Hangzhou Normal University","ror":"https://ror.org/014v1mr15","country_code":"CN","type":"education","lineage":["https://openalex.org/I163151501"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dandan Ding","raw_affiliation_strings":["Hangzhou Normal University,Hangzhou,China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Normal University,Hangzhou,China","institution_ids":["https://openalex.org/I163151501"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073914656","display_name":"Zhan Ma","orcid":"https://orcid.org/0000-0003-3686-4057"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhan Ma","raw_affiliation_strings":["Nanjing University,Nanjing,China"],"affiliations":[{"raw_affiliation_string":"Nanjing University,Nanjing,China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5016588601"],"corresponding_institution_ids":["https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":0.391,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61596681,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"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/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.7785000205039978,"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/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.7785000205039978,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.6926000118255615,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T10638","display_name":"Optical measurement and interference techniques","score":0.6819000244140625,"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/computer-science","display_name":"Computer science","score":0.7649255990982056},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4442984461784363},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4058288037776947},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.34475189447402954},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3333887457847595},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.074908047914505}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7649255990982056},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4442984461784363},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4058288037776947},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.34475189447402954},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3333887457847595},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.074908047914505},{"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/vcip63160.2024.10849821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip63160.2024.10849821","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2738551266","https://openalex.org/W2901982540","https://openalex.org/W3215769467","https://openalex.org/W4251695946","https://openalex.org/W4385318467","https://openalex.org/W4391800855","https://openalex.org/W4400403028","https://openalex.org/W4402557597","https://openalex.org/W4402571450","https://openalex.org/W4402716359","https://openalex.org/W4402716405","https://openalex.org/W4402726969","https://openalex.org/W4402727236","https://openalex.org/W4402727321","https://openalex.org/W4402727715","https://openalex.org/W4402753826","https://openalex.org/W4402754225","https://openalex.org/W4403780676","https://openalex.org/W4404024976","https://openalex.org/W4404545288","https://openalex.org/W4404725206","https://openalex.org/W4405867686","https://openalex.org/W6631190155","https://openalex.org/W6858555619","https://openalex.org/W6858851893","https://openalex.org/W6869436445","https://openalex.org/W6872722020"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"As":[0],"a":[1,44,56,61,88,98,107],"promising":[2],"technique":[3],"for":[4,66,120],"3D":[5,7],"representation,":[6,72],"Gaussian":[8],"Splatting":[9],"(3DGS)":[10],"offers":[11],"fast":[12],"rendering":[13],"speed":[14],"and":[15,26,59,109,118,141,150],"high":[16],"fidelity":[17],"while":[18],"generating":[19],"large":[20],"data":[21,77],"volumes.":[22],"This":[23],"challenges":[24],"storage":[25],"transmission,":[27],"so":[28],"an":[29],"efficient":[30],"compression":[31,78,103,143,166],"solution":[32],"is":[33,81,95],"required.":[34],"Existing":[35],"implicit":[36],"methods":[37],"require":[38,160],"pre-scene":[39],"optimization":[40,46],"(online),":[41],"leading":[42],"to":[43,83,112,146,163],"long":[45],"time.":[47],"By":[48],"contrast,":[49],"this":[50],"paper":[51],"regards":[52],"the":[53,70,76,147,165],"3DGS":[54,71,132,149],"as":[55],"point":[57,101],"cloud":[58,102],"pre-trains":[60],"generalizable":[62],"(offline)":[63],"neural":[64,92],"coder":[65,93],"compression.":[67],"After":[68],"obtaining":[69],"we":[73],"focus":[74],"on":[75],"process,":[79],"which":[80,105],"friendly":[82],"applications":[84],"already":[85],"equipped":[86],"with":[87],"PCC":[89],"codec.":[90],"The":[91],"employed":[94],"extended":[96],"from":[97],"typical":[99],"AIbased":[100],"method,":[104],"uses":[106],"multiscale":[108],"multistage":[110],"framework":[111],"exploit":[113],"spatial":[114],"correlations":[115],"across":[116],"scales":[117],"stages":[119],"conditional":[121],"coding.":[122],"Experimental":[123],"results":[124],"show":[125],"that":[126],"our":[127,156],"method":[128],"significantly":[129],"outperforms":[130],"existing":[131],"representations":[133],"without":[134],"compromising":[135],"fidelity,":[136],"achieving":[137],"more":[138],"than":[139],"39\u00d7":[140],"6.8\u00d7":[142],"ratio":[144],"compared":[145],"original":[148],"SOTA":[151],"Scaffold-GS,":[152],"respectively.":[153],"More":[154],"importantly,":[155],"approach":[157],"does":[158],"not":[159],"additional":[161],"time":[162],"optimize":[164],"model.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
