{"id":"https://openalex.org/W7164574437","doi":"https://doi.org/10.1109/tci.2026.3703182","title":"NormalMVS: Learning Efficient Geometry-Aware Multiview Stereo With Surface Normal Priors","display_name":"NormalMVS: Learning Efficient Geometry-Aware Multiview Stereo With Surface Normal Priors","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7164574437","doi":"https://doi.org/10.1109/tci.2026.3703182"},"language":null,"primary_location":{"id":"doi:10.1109/tci.2026.3703182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2026.3703182","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2334-0118","2573-0436"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Imaging","raw_type":"journal-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/A5019386082","display_name":"Xingchen Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingchen Lv","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044948606","display_name":"Qingjie Zhao","orcid":"https://orcid.org/0000-0002-6955-4170"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingjie Zhao","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6955-4170","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060657278","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0002-1206-8729"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["Beijing Institute of Control Engineering, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Control Engineering, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"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":0.75910133,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"1088","last_page":"1099"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9096999764442444,"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":0.9096999764442444,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.033399999141693115,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.01209999993443489,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.5825999975204468},{"id":"https://openalex.org/keywords/normal","display_name":"Normal","score":0.40560001134872437},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3919000029563904},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.3840999901294708},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36910000443458557},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.35519999265670776},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.313400000333786},{"id":"https://openalex.org/keywords/stereopsis","display_name":"Stereopsis","score":0.313400000333786}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7257999777793884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6880000233650208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6029999852180481},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5825999975204468},{"id":"https://openalex.org/C118732077","wikidata":"https://www.wikidata.org/wiki/Q273176","display_name":"Normal","level":3,"score":0.40560001134872437},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3919000029563904},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.3840999901294708},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36910000443458557},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.35519999265670776},{"id":"https://openalex.org/C68537008","wikidata":"https://www.wikidata.org/wiki/Q247932","display_name":"Stereopsis","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.313400000333786},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31310001015663147},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C102094743","wikidata":"https://www.wikidata.org/wiki/Q133871","display_name":"Normal distribution","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.2799000144004822},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27950000762939453},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.26420000195503235},{"id":"https://openalex.org/C20885615","wikidata":"https://www.wikidata.org/wiki/Q825595","display_name":"Surface reconstruction","level":3,"score":0.25949999690055847},{"id":"https://openalex.org/C2987632653","wikidata":"https://www.wikidata.org/wiki/Q7611220","display_name":"Stereo image","level":3,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tci.2026.3703182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2026.3703182","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2334-0118","2573-0436"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Learning-based":[0],"multiview":[1],"stereo":[2],"(MVS)":[3],"has":[4],"achieved":[5],"remarkable":[6],"progress,":[7],"largely":[8],"driven":[9],"by":[10,128],"cascade-based":[11],"architectures.":[12],"However,":[13],"existing":[14,176],"methods":[15,177],"inevitably":[16],"suffer":[17],"from":[18],"error":[19,100],"accumulation":[20],"across":[21],"stages":[22],"because":[23],"of":[24,46,122,157,180],"simple":[25],"upsampling.":[26],"Furthermore,":[27],"relying":[28],"solely":[29],"on":[30,119,162],"RGB":[31,85],"images":[32],"often":[33],"leads":[34],"to":[35,70,94,149],"photometric":[36,96],"ambiguity":[37],"in":[38,51,178],"textureless":[39],"or":[40],"non-Lambertian":[41],"regions":[42],"and":[43,86,89,125,142,154,168,186],"a":[44,77,104,129,139,143],"lack":[45],"explicit":[47],"3D":[48,158],"constraints,":[49],"resulting":[50],"erroneous":[52],"correspondences.":[53],"To":[54,98],"address":[55],"these":[56],"challenges,":[57],"we":[58,75,102],"propose":[59],"NormalMVS,":[60],"an":[61],"efficient":[62],"framework":[63],"that":[64,82,134,172],"explicitly":[65],"incorporates":[66],"surface":[67],"normal":[68,87],"priors":[69],"enhance":[71],"reconstruction":[72,184],"quality.":[73],"Specifically,":[74],"design":[76,103],"geometry-aware":[78],"fusion":[79],"(GAF)":[80],"module":[81],"synergistically":[83],"combines":[84],"features":[88],"extracts":[90],"discriminative":[91],"geometric":[92,136],"cues":[93],"resolve":[95],"ambiguities.":[97],"mitigate":[99],"propagation,":[101],"normal-guided":[105],"depth":[106,117],"refinement":[107],"(NGDR)":[108],"module.":[109],"Unlike":[110],"conventional":[111],"bilinear":[112],"interpolation,":[113],"NGDR":[114],"refines":[115],"upsampled":[116],"maps":[118],"the":[120,152,163],"basis":[121],"local":[123],"coplanarity":[124],"is":[126],"supervised":[127],"novel":[130],"neighbor-weighted":[131],"consistency":[132],"loss":[133],"enforces":[135],"coherence.":[137],"Additionally,":[138],"four-stage":[140],"architecture":[141],"sparse":[144],"sampling":[145],"strategy":[146],"are":[147],"introduced":[148],"significantly":[150],"reduce":[151],"computational":[153],"memory":[155],"overhead":[156],"CNNs.":[159],"Extensive":[160],"experiments":[161],"DTU,":[164],"Tanks":[165],"&":[166],"Temples,":[167],"ETH3D":[169],"benchmarks":[170],"demonstrate":[171],"NormalMVS":[173],"outperforms":[174],"most":[175],"terms":[179],"efficiency,":[181],"effectively":[182],"balancing":[183],"quality":[185],"resource":[187],"consumption.":[188]},"counts_by_year":[],"updated_date":"2026-06-26T06:17:10.115597","created_date":"2026-06-13T00:00:00"}
