{"id":"https://openalex.org/W4408353225","doi":"https://doi.org/10.1109/icassp49660.2025.10890402","title":"Mixed Gaussian Splatting for High-Quality Rendering and Reconstruction","display_name":"Mixed Gaussian Splatting for High-Quality Rendering and Reconstruction","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408353225","doi":"https://doi.org/10.1109/icassp49660.2025.10890402"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10890402","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890402","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5100320478","display_name":"Shuai Liu","orcid":"https://orcid.org/0000-0002-0699-2296"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuai Liu","raw_affiliation_strings":["Shanghai Jiao Tong Univeristy,Department of Automation,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong Univeristy,Department of Automation,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069926649","display_name":"Jianyu Ding","orcid":"https://orcid.org/0000-0002-4886-9667"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianyu Ding","raw_affiliation_strings":["Shanghai Jiao Tong Univeristy,Department of Automation,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong Univeristy,Department of Automation,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068383847","display_name":"Jie Yang","orcid":"https://orcid.org/0000-0002-8244-2181"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Yang","raw_affiliation_strings":["Shanghai Jiao Tong Univeristy,Department of Automation,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong Univeristy,Department of Automation,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062908102","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0003-2968-2888"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Shanghai Jiao Tong Univeristy,Department of Automation,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong Univeristy,Department of Automation,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100320478"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":6.3135,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.9496124,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9771999716758728,"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"}},"topics":[{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9771999716758728,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7965134382247925},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5848075747489929},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.5691860318183899},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4184485673904419},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32155776023864746}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7965134382247925},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5848075747489929},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.5691860318183899},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4184485673904419},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32155776023864746},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10890402","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10890402","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2471962767","https://openalex.org/W2738551266","https://openalex.org/W3215769467","https://openalex.org/W4200150166","https://openalex.org/W4221151978","https://openalex.org/W4232452729","https://openalex.org/W4385318467","https://openalex.org/W4386066812","https://openalex.org/W4388482374","https://openalex.org/W4389665446","https://openalex.org/W4393248012","https://openalex.org/W4400581036","https://openalex.org/W4400581059","https://openalex.org/W4402704609","https://openalex.org/W4402716153","https://openalex.org/W4402716405","https://openalex.org/W4404132771","https://openalex.org/W4404524486","https://openalex.org/W4404526364","https://openalex.org/W4409264028","https://openalex.org/W6747827861","https://openalex.org/W6797770180","https://openalex.org/W6838746019","https://openalex.org/W6859253671","https://openalex.org/W6863557674","https://openalex.org/W6868651516","https://openalex.org/W6869209665","https://openalex.org/W6869314603"],"related_works":["https://openalex.org/W291250033","https://openalex.org/W2035757446","https://openalex.org/W3137044537","https://openalex.org/W2008385118","https://openalex.org/W880955280","https://openalex.org/W2106647072","https://openalex.org/W2172753644","https://openalex.org/W2170209930","https://openalex.org/W4246858109","https://openalex.org/W54172855"],"abstract_inverted_index":{"3D":[0,73,82,101],"Gaussian":[1,61,102],"Splatting":[2,62],"(3DGS)":[3],"has":[4],"demonstrated":[5],"impressive":[6],"novel":[7],"view":[8],"synthesis":[9],"with":[10],"rapid":[11],"rendering":[12,35,52,119],"speed.":[13],"Current":[14],"works":[15],"explore":[16],"its":[17],"application":[18],"to":[19,22],"geometric":[20],"reconstruction":[21,38,47,71,124],"fully":[23],"release":[24],"the":[25,34,37,51,95,126],"potential":[26],"of":[27,97],"3DGS.":[28],"However,":[29],"a":[30],"trade-off":[31],"exists":[32],"between":[33],"and":[36,72,88,100,121],"when":[39],"representing":[40],"real-world":[41,112],"scenes,":[42],"as":[43],"achieving":[44],"detailed":[45,122],"surface":[46,70],"can":[48],"often":[49],"compromise":[50],"quality.":[53],"To":[54],"address":[55],"this":[56],"issue,":[57],"we":[58],"introduce":[59],"Mixed":[60],"(MixedGS)":[63],"which":[64],"combines":[65],"2D":[66,99],"Gaussians":[67,74,84],"for":[68,75],"accurate":[69],"high-fidelity":[76],"rendering.":[77],"With":[78],"anchor":[79],"point":[80],"initialization,":[81],"neural":[83],"derivation,":[85],"contribution-based":[86],"densification":[87],"joint":[89],"supervision,":[90],"our":[91,115],"method":[92,116],"effectively":[93],"leverages":[94],"advantages":[96],"both":[98],"primitives":[103],"while":[104],"mitigating":[105],"their":[106],"limitations.":[107],"We":[108],"demonstrate":[109],"on":[110],"diverse":[111],"scenes":[113],"that":[114],"achieves":[117],"competitive":[118],"quality":[120],"geometry":[123],"at":[125],"same":[127],"time.":[128]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2025-10-10T00:00:00"}