{"id":"https://openalex.org/W4415537733","doi":"https://doi.org/10.1145/3746027.3755720","title":"TriGS: Tri-consistency 3D Gaussian Splatting from Sparse and Unposed Views","display_name":"TriGS: Tri-consistency 3D Gaussian Splatting from Sparse and Unposed Views","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415537733","doi":"https://doi.org/10.1145/3746027.3755720"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755720","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755720","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","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/A5112099675","display_name":"Chi Yo Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chi Huang","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0006-7379-5491","affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002550969","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0002-0548-6121"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-0548-6121","affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112446139","display_name":"Qian Zhang","orcid":"https://orcid.org/0000-0001-5252-1287"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Zhang","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-5252-1287","affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100341109","display_name":"Nan Li","orcid":"https://orcid.org/0000-0002-6723-1124"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Li","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-6723-1124","affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110801074","display_name":"Yipu Gong","orcid":"https://orcid.org/0000-0002-7827-8809"},"institutions":[{"id":"https://openalex.org/I4210160117","display_name":"Dunhuang Research Academy","ror":"https://ror.org/05j1pnm38","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210160117"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yipu Gong","raw_affiliation_strings":["Dunhuang Academy, Dunhuang, China"],"raw_orcid":"https://orcid.org/0000-0002-7827-8809","affiliations":[{"raw_affiliation_string":"Dunhuang Academy, Dunhuang, China","institution_ids":["https://openalex.org/I4210160117"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103641900","display_name":"Xiaowei Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210160117","display_name":"Dunhuang Research Academy","ror":"https://ror.org/05j1pnm38","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210160117"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Wang","raw_affiliation_strings":["Dunhuang Academy, Dunhuang, China"],"raw_orcid":"https://orcid.org/0009-0006-4251-8117","affiliations":[{"raw_affiliation_string":"Dunhuang Academy, Dunhuang, China","institution_ids":["https://openalex.org/I4210160117"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100721881","display_name":"Wei Feng","orcid":"https://orcid.org/0000-0003-3809-1086"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Feng","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-3809-1086","affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5112099675"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":1.0943,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83003081,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"699","last_page":"708"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9995999932289124,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9995999932289124,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9987000226974487,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.6262999773025513},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5231000185012817},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4837000072002411},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4830999970436096},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.38670000433921814},{"id":"https://openalex.org/keywords/gaussian-network-model","display_name":"Gaussian network model","score":0.352400004863739},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.33399999141693115},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.3215999901294708}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7930999994277954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6563000082969666},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.6262999773025513},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.551800012588501},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5231000185012817},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4837000072002411},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4830999970436096},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.38670000433921814},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.352400004863739},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.33399999141693115},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3215999901294708},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.30219998955726624},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.2612999975681305},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26010000705718994},{"id":"https://openalex.org/C36816356","wikidata":"https://www.wikidata.org/wiki/Q16911860","display_name":"3D rendering","level":3,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755720","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755720","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","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":17,"referenced_works":["https://openalex.org/W2085905957","https://openalex.org/W2133665775","https://openalex.org/W2738551266","https://openalex.org/W2962785568","https://openalex.org/W2963516811","https://openalex.org/W3109585842","https://openalex.org/W3174541782","https://openalex.org/W3176368002","https://openalex.org/W4385318467","https://openalex.org/W4386065597","https://openalex.org/W4386076472","https://openalex.org/W4390874571","https://openalex.org/W4402660132","https://openalex.org/W4402715996","https://openalex.org/W4402727067","https://openalex.org/W4402754045","https://openalex.org/W4403791234"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"advances":[1],"in":[2,30,141],"3D":[3,7,42],"scene":[4],"representation,":[5],"particularly":[6],"Gaussian":[8,43,125],"Splatting":[9,44],"(3DGS),":[10],"have":[11],"demonstrated":[12],"remarkable":[13],"photorealistic":[14],"rendering":[15,110,117],"capabilities.":[16],"However,":[17],"the":[18,70,177,191],"heavy":[19],"reliance":[20,192],"on":[21,156,171,193],"dense":[22],"and":[23,33,55,61,105,127,134,159,200],"precisely":[24],"calibrated":[25],"camera":[26,56,78,128],"configurations":[27],"limits":[28],"effectiveness":[29,178],"sparse":[31,60,199],"view":[32,202],"unposed":[34,62,201],"scenarios.":[35],"In":[36],"this":[37,92],"paper,":[38],"we":[39,94,144],"present":[40],"Tri-consistency":[41],"(dubbed":[45],"TriGS),":[46],"a":[47,187],"novel":[48],"framework":[49],"that":[50,150],"jointly":[51,123],"optimizes":[52],"3DGS":[53],"parameters":[54],"poses":[57,79,129],"only":[58,197],"from":[59],"images":[63],"via":[64],"triple":[65],"consistency":[66,97,164],"supervisions":[67],"coupled":[68],"with":[69,112],"adaptive":[71,147],"regularization":[72,148],"strategy.":[73],"We":[74],"first":[75],"estimate":[76],"coarse":[77],"by":[80,130],"exploiting":[81],"3DGS's":[82],"anisotropic":[83],"properties":[84],"through":[85,99,165],"iterative":[86],"relative":[87],"pose":[88,195],"optimization.":[89],"Building":[90],"upon":[91],"foundation,":[93],"introduce":[95],"cross-view":[96],"enforcement":[98],"synchronized":[100],"photometric":[101],"color,":[102],"geometric":[103],"structure,":[104],"deep":[106,166],"feature,":[107],"effectively":[108],"resolving":[109],"ambiguities":[111],"auxiliary":[113],"supervisions.":[114],"A":[115],"unified":[116],"paradigm":[118],"is":[119],"also":[120],"proposed":[121],"to":[122,185],"refine":[124],"primitives":[126],"transforming":[131],"positions,":[132],"covariances,":[133],"spherical":[135],"harmonics.":[136],"To":[137],"combat":[138],"overfitting":[139],"inherent":[140],"joint":[142],"optimization,":[143],"devise":[145],"an":[146],"mechanism":[149],"strategically":[151],"samples":[152],"hard":[153],"viewpoints":[154],"based":[155],"baseline":[157],"distances":[158],"training":[160],"dynamics,":[161],"enforcing":[162],"projection":[163],"feature":[167],"priors.":[168],"Extensive":[169],"experiments":[170],"multiple":[172],"challenging":[173],"real-world":[174],"datasets":[175],"validate":[176],"of":[179],"TriGS,":[180],"which":[181],"achieves":[182],"satisfactory":[183],"results":[184],"set":[186],"new":[188],"state-of-the-art":[189],"without":[190],"external":[194],"priors":[196],"under":[198],"inputs.":[203]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-25T00:00:00"}