{"id":"https://openalex.org/W7160307920","doi":"https://doi.org/10.1109/wacv61042.2026.00074","title":"Joint Modeling of Corruption-Driven and Information-Limited Uncertainty for Robust 3D Gaussian Splatting","display_name":"Joint Modeling of Corruption-Driven and Information-Limited Uncertainty for Robust 3D Gaussian Splatting","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7160307920","doi":"https://doi.org/10.1109/wacv61042.2026.00074"},"language":null,"primary_location":{"id":"doi:10.1109/wacv61042.2026.00074","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5083772315","display_name":"Zeji Hui","orcid":null},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zeji Hui","raw_affiliation_strings":["RMIT University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RMIT University","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064997605","display_name":"Amirali Khodadadian Gostar","orcid":"https://orcid.org/0000-0002-4800-6554"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Amirali Khodadadian Gostar","raw_affiliation_strings":["RMIT University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RMIT University","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060353361","display_name":"WeiQin Chuah","orcid":"https://orcid.org/0000-0001-6020-4660"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"WeiQin Chuah","raw_affiliation_strings":["RMIT University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RMIT University","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130381245","display_name":"Alireza Bab-Hadiashar","orcid":null},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Alireza Bab-Hadiashar","raw_affiliation_strings":["RMIT University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RMIT University","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135292707","display_name":"Ruwan Tennakoon","orcid":null},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ruwan Tennakoon","raw_affiliation_strings":["RMIT University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RMIT University","institution_ids":["https://openalex.org/I82951845"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82951845"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45324044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"688","last_page":"697"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.09220000356435776,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.09220000356435776,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.048500001430511475,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.046799998730421066,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/joint","display_name":"Joint (building)","score":0.5360999703407288},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3506999909877777},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.3167000114917755},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.303600013256073},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.2980000078678131},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.2842000126838684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6352999806404114},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5360999703407288},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4616999924182892},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4115000069141388},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3506999909877777},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3167000114917755},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.303600013256073},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2922999858856201},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2842000126838684},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.26089999079704285},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv61042.2026.00074","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00074","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7434265613555908,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W3109585842","https://openalex.org/W3159481202","https://openalex.org/W3177583232","https://openalex.org/W3196914928","https://openalex.org/W3203570626","https://openalex.org/W4221151978","https://openalex.org/W4312790183","https://openalex.org/W4312933868","https://openalex.org/W4313137167","https://openalex.org/W4385318467","https://openalex.org/W4386076007","https://openalex.org/W4390874091","https://openalex.org/W4390874575","https://openalex.org/W4402703102","https://openalex.org/W4402716301","https://openalex.org/W4402727269","https://openalex.org/W4402754077","https://openalex.org/W4402774473","https://openalex.org/W4403843633","https://openalex.org/W4403888264","https://openalex.org/W4403888693","https://openalex.org/W4404545287","https://openalex.org/W4408955770","https://openalex.org/W4409704677","https://openalex.org/W4410730192","https://openalex.org/W4413147421","https://openalex.org/W4413147638","https://openalex.org/W7160083245"],"related_works":[],"abstract_inverted_index":{"Real-time":[0],"3D":[1],"Gaussian":[2],"Splatting":[3],"(3DGS)":[4],"has":[5],"emerged":[6],"as":[7,61,108,110],"an":[8],"efficient,":[9],"high-fidelity":[10],"alternative":[11],"to":[12,57,118],"neural":[13],"radiance":[14],"fields":[15],"for":[16],"novel":[17],"view":[18,47],"synthesis,":[19],"enabling":[20],"second-scale":[21],"training":[22,105],"and":[23,65,92,113,145,157,163],"rendering":[24],"via":[25],"GPU":[26],"rasterization.":[27],"However,":[28],"when":[29],"input":[30],"image":[31],"collections":[32],"contain":[33],"transient":[34,88],"disturbances":[35],"(e.g.,":[36],"dynamic":[37,143],"objects,":[38],"exposure":[39],"variations,":[40],"motion":[41],"blur)":[42],"or":[43,89,133],"suffer":[44],"from":[45],"sparse":[46,146],"coverage":[48],"at":[49],"scene":[50],"boundaries,":[51],"3DGS":[52,156],"performance":[53],"degrades":[54],"significantly":[55],"due":[56],"reconstruction":[58,164],"artifacts":[59],"such":[60],"ghosting,":[62],"floating":[63],"points,":[64],"blurred":[66],"surfaces.":[67],"In":[68],"this":[69],"work,":[70],"we":[71],"present":[72],"a":[73,124],"unified":[74],"framework":[75],"that":[76,150],"jointly":[77],"addresses":[78],"two":[79,139],"types":[80],"of":[81,116],"artifacts:":[82],"(1)":[83],"corruption-driven":[84],"artifacts,":[85,95],"caused":[86,96],"by":[87,97],"occluded":[90],"content;":[91],"(2)":[93],"information-limited":[94],"insufficient":[98],"multi-view":[99],"observations.":[100],"Our":[101],"method":[102],"leverages":[103],"the":[104,111],"gradient":[106],"signal,":[107],"well":[109],"shape":[112],"spatial":[114],"distribution":[115],"Gaussians,":[117],"adaptively":[119],"suppress":[120],"unreliable":[121],"splats":[122],"through":[123],"soft-masking":[125],"strategy,":[126],"without":[127],"relying":[128],"on":[129,138],"any":[130],"pretrained":[131],"segmentation":[132],"feature":[134],"networks.":[135],"Extensive":[136],"experiments":[137],"real-world":[140],"datasets":[141],"with":[142],"scenes":[144],"camera":[147],"trajectories":[148],"demonstrate":[149],"our":[151],"approach":[152],"outperforms":[153],"state-of-the-art":[154],"robust":[155],"uncertainty-pruning":[158],"techniques":[159],"in":[160],"artifact":[161],"suppression":[162],"fidelity,":[165],"while":[166],"preserving":[167],"real-time":[168],"performance.":[169]},"counts_by_year":[],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2026-05-06T00:00:00"}
