{"id":"https://openalex.org/W4415346749","doi":"https://doi.org/10.1109/iccv51701.2025.02408","title":"A View-Consistent Sampling Method for Regularized Training of Neural Radiance Fields","display_name":"A View-Consistent Sampling Method for Regularized Training of Neural Radiance Fields","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4415346749","doi":"https://doi.org/10.1109/iccv51701.2025.02408"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.02408","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.02408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.04408","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043378752","display_name":"Aoxiang Fan","orcid":"https://orcid.org/0000-0002-2877-9795"},"institutions":[{"id":"https://openalex.org/I1295703814","display_name":"World Vision","ror":"https://ror.org/01s0tbj55","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1295703814","https://openalex.org/I4210093867"]},{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH","US"],"is_corresponding":false,"raw_author_name":"Aoxiang Fan","raw_affiliation_strings":["EPFL,Computer Vision Laboratory,Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EPFL,Computer Vision Laboratory,Switzerland","institution_ids":["https://openalex.org/I5124864","https://openalex.org/I1295703814"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008484135","display_name":"Corentin Dumery","orcid":"https://orcid.org/0000-0001-5314-7979"},"institutions":[{"id":"https://openalex.org/I1295703814","display_name":"World Vision","ror":"https://ror.org/01s0tbj55","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1295703814","https://openalex.org/I4210093867"]},{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH","US"],"is_corresponding":false,"raw_author_name":"Corentin Dumery","raw_affiliation_strings":["EPFL,Computer Vision Laboratory,Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EPFL,Computer Vision Laboratory,Switzerland","institution_ids":["https://openalex.org/I5124864","https://openalex.org/I1295703814"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064916555","display_name":"Nicolas Talabot","orcid":null},"institutions":[{"id":"https://openalex.org/I1295703814","display_name":"World Vision","ror":"https://ror.org/01s0tbj55","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1295703814","https://openalex.org/I4210093867"]},{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH","US"],"is_corresponding":false,"raw_author_name":"Nicolas Talabot","raw_affiliation_strings":["EPFL,Computer Vision Laboratory,Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EPFL,Computer Vision Laboratory,Switzerland","institution_ids":["https://openalex.org/I5124864","https://openalex.org/I1295703814"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038674741","display_name":"Pascal Fua","orcid":"https://orcid.org/0000-0002-6702-9970"},"institutions":[{"id":"https://openalex.org/I1295703814","display_name":"World Vision","ror":"https://ror.org/01s0tbj55","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1295703814","https://openalex.org/I4210093867"]},{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH","US"],"is_corresponding":false,"raw_author_name":"Pascal Fua","raw_affiliation_strings":["EPFL,Computer Vision Laboratory,Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EPFL,Computer Vision Laboratory,Switzerland","institution_ids":["https://openalex.org/I5124864","https://openalex.org/I1295703814"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15015238,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"25961","last_page":"25971"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9666000008583069,"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/T10320","display_name":"Neural Networks and Applications","score":0.9666000008583069,"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/regularization","display_name":"Regularization (linguistics)","score":0.7164999842643738},{"id":"https://openalex.org/keywords/radiance","display_name":"Radiance","score":0.628600001335144},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4555000066757202},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.44589999318122864},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44029998779296875},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.415800005197525}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7164999842643738},{"id":"https://openalex.org/C23690007","wikidata":"https://www.wikidata.org/wiki/Q1411145","display_name":"Radiance","level":2,"score":0.628600001335144},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6208000183105469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6108999848365784},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4555000066757202},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.44589999318122864},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44029998779296875},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.415800005197525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4124000072479248},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.41119998693466187},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3578999936580658},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.34060001373291016},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29670000076293945},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2526000142097473}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccv51701.2025.02408","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.02408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2507.04408","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.04408","pdf_url":"https://arxiv.org/pdf/2507.04408","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.04408","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.04408","pdf_url":"https://arxiv.org/pdf/2507.04408","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Neural":[0],"Radiance":[1],"Fields":[2],"(NeRF)":[3],"has":[4],"emerged":[5],"as":[6,180,182],"a":[7,52,133],"compelling":[8],"framework":[9],"for":[10,63,149],"scene":[11],"representation":[12],"and":[13,97],"3D":[14,41,112],"recovery.":[15],"To":[16],"improve":[17],"its":[18],"performance":[19],"on":[20,125,157],"real-world":[21],"data,":[22],"depth":[23,34,55,79,184],"regularizations":[24,148],"have":[25],"proven":[26],"to":[27,72,82,144],"be":[28,58],"the":[29,54,87,105,117,126,141,151],"most":[30],"effective":[31,147],"ones.":[32],"However,":[33],"estimation":[35],"models":[36,103],"not":[37],"only":[38],"require":[39],"expensive":[40],"supervision":[42],"in":[43,60,138],"training,":[44],"but":[45],"also":[46,131],"suffer":[47],"from":[48,101,109,116,160],"generalization":[49],"issues.":[50],"As":[51],"result,":[53],"estimations":[56,81],"can":[57,168],"erroneous":[59],"practice,":[61],"especially":[62],"outdoor":[64],"unbounded":[65],"scenes.":[66],"In":[67],"this":[68],"paper,":[69],"we":[70],"propose":[71],"employ":[73],"view-consistent":[74],"distributions":[75],"instead":[76],"of":[77,128],"fixed":[78],"value":[80],"regularize":[83],"NeRF":[84,178],"training.":[85],"Specifically,":[86],"distribution":[88],"is":[89,123],"computed":[90],"by":[91],"utilizing":[92],"both":[93],"low-level":[94],"color":[95],"features":[96,100],"high-level":[98],"distilled":[99],"foundation":[102],"at":[104],"projected":[106],"2D":[107],"pixel-locations":[108],"per-ray":[110],"sampled":[111],"points.":[113],"By":[114],"sampling":[115,142],"view-consistency":[118],"distributions,":[119],"an":[120],"implicit":[121],"regularization":[122,185],"imposed":[124],"training":[127],"NeRF.":[129],"We":[130],"utilize":[132],"depth-pushing":[134],"loss":[135],"that":[136,164],"works":[137],"conjunction":[139],"with":[140],"technique":[143],"jointly":[145],"provide":[146],"eliminating":[150],"failure":[152],"modes.":[153],"Extensive":[154],"experiments":[155],"conducted":[156],"various":[158],"scenes":[159],"public":[161],"datasets":[162],"demonstrate":[163],"our":[165],"proposed":[166],"method":[167],"generate":[169],"significantly":[170],"better":[171],"novel":[172],"view":[173],"synthesis":[174],"results":[175],"than":[176],"state-of-the-art":[177],"variants":[179],"well":[181],"different":[183],"methods.":[186]},"counts_by_year":[],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-20T00:00:00"}
