{"id":"https://openalex.org/W4405253446","doi":"https://doi.org/10.1109/3dv69130.2026.00060","title":"Prism: Semi-Supervised Multi-View Stereo with Monocular Structure Priors","display_name":"Prism: Semi-Supervised Multi-View Stereo with Monocular Structure Priors","publication_year":2026,"publication_date":"2026-03-20","ids":{"openalex":"https://openalex.org/W4405253446","doi":"https://doi.org/10.1109/3dv69130.2026.00060"},"language":"en","primary_location":{"id":"doi:10.1109/3dv69130.2026.00060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on 3D Vision (3DV)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2412.05771","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043001458","display_name":"Alex Rich","orcid":"https://orcid.org/0009-0009-0512-310X"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alex Rich","raw_affiliation_strings":["University of California,Santa Barbara"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Santa Barbara","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002901804","display_name":"Noah Stier","orcid":"https://orcid.org/0000-0001-9602-4637"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Noah Stier","raw_affiliation_strings":["University of California,Santa Barbara"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Santa Barbara","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087948617","display_name":"Pradeep Sen","orcid":"https://orcid.org/0000-0002-8042-924X"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pradeep Sen","raw_affiliation_strings":["University of California,Santa Barbara"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Santa Barbara","institution_ids":["https://openalex.org/I154570441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028885566","display_name":"Tobias H\u00f6llerer","orcid":"https://orcid.org/0000-0002-6240-0291"},"institutions":[{"id":"https://openalex.org/I154570441","display_name":"University of California, Santa Barbara","ror":"https://ror.org/02t274463","country_code":"US","type":"education","lineage":["https://openalex.org/I154570441"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tobias H\u00d6llerer","raw_affiliation_strings":["University of California,Santa Barbara"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California,Santa Barbara","institution_ids":["https://openalex.org/I154570441"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00315011,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"565","last_page":"575"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9990000128746033,"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":0.9990000128746033,"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/T12983","display_name":"Satellite Image Processing and Photogrammetry","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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":0.9836000204086304,"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/prior-probability","display_name":"Prior probability","score":0.839040994644165},{"id":"https://openalex.org/keywords/prism","display_name":"Prism","score":0.7645635604858398},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6626851558685303},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.6441164612770081},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5358359217643738},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5041524171829224},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.2231685221195221},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.13769999146461487},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13608121871948242}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.839040994644165},{"id":"https://openalex.org/C67666897","wikidata":"https://www.wikidata.org/wiki/Q165896","display_name":"Prism","level":2,"score":0.7645635604858398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6626851558685303},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.6441164612770081},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5358359217643738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5041524171829224},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.2231685221195221},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.13769999146461487},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13608121871948242}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/3dv69130.2026.00060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv69130.2026.00060","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on 3D Vision (3DV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2412.05771","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.05771","pdf_url":"https://arxiv.org/pdf/2412.05771","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2412.05771","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2412.05771","pdf_url":null,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2412.05771","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2412.05771","pdf_url":"https://arxiv.org/pdf/2412.05771","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4405253446.pdf"},"referenced_works_count":0,"referenced_works":[],"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":{"The":[0],"promise":[1],"of":[2,27,91,109],"unsupervised":[3,157],"multi-view":[4],"stereo":[5],"(MVS)":[6],"is":[7,87,163],"to":[8,44,46,62,84,113,171],"leverage":[9],"large":[10,150],"unlabeled":[11,118,174],"datasets,":[12],"yet":[13],"current":[14,156],"methods":[15],"underperform":[16],"when":[17],"training":[18,182],"on":[19,40,64,101,117],"difficult":[20],"data,":[21],"such":[22],"as":[23],"handheld":[24],"smartphone":[25,175],"videos":[26,176],"indoor":[28],"scenes.":[29],"Meanwhile,":[30],"high-quality":[31],"synthetic":[32,74,103,179],"datasets":[33,42,180],"are":[34],"available":[35],"but":[36],"MVS":[37,115,128,160,183],"networks":[38],"trained":[39,100],"these":[41],"fail":[43],"generalize":[45],"realworld":[47,81],"examples.":[48],"To":[49],"bridge":[50],"this":[51,110],"gap,":[52],"we":[53,125,146],"propose":[54],"a":[55,88,133,138,165],"semisupervised":[56],"learning":[57],"framework":[58,86],"that":[59,93],"allows":[60],"us":[61],"train":[63],"real":[65],"and":[66,129,137,152,158,177],"rendered":[67],"images":[68],"jointly,":[69],"capturing":[70],"structural":[71],"priors":[72],"from":[73],"data":[75],"while":[76],"ensuring":[77],"parity":[78],"with":[79],"the":[80,102,106,114,127,169],"domain.":[82],"Central":[83],"our":[85],"novel":[89],"set":[90],"losses":[92],"leverages":[94],"powerful":[95],"existing":[96],"monocular":[97,130],"relativedepth":[98],"estimators":[99],"dataset,":[104],"transferring":[105],"rich":[107],"structure":[108],"relative":[111],"depth":[112],"predictions":[116,131],"data.":[119],"Inspired":[120],"by":[121],"perceptual":[122],"image":[123],"metrics,":[124],"compare":[126],"via":[132],"deep":[134],"feature":[135],"loss":[136],"multi-scale":[139],"statistical":[140],"loss.":[141],"Our":[142],"full":[143],"framework,":[144],"which":[145],"call":[147],"Prism,":[148],"achieves":[149],"quantitative":[151],"qualitative":[153],"improvements":[154],"over":[155],"synthetic-supervised":[159],"networks.":[161,184],"This":[162],"quite":[164],"useful":[166],"result,":[167],"opening":[168],"door":[170],"using":[172],"both":[173],"photorealistic":[178],"for":[181]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}