{"id":"https://openalex.org/W4294672564","doi":"https://doi.org/10.1109/rcar54675.2022.9872231","title":"Two-stage Self-supervised MVS Network using Adaptive Depth Sampling","display_name":"Two-stage Self-supervised MVS Network using Adaptive Depth Sampling","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4294672564","doi":"https://doi.org/10.1109/rcar54675.2022.9872231"},"language":"en","primary_location":{"id":"doi:10.1109/rcar54675.2022.9872231","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rcar54675.2022.9872231","pdf_url":null,"source":{"id":"https://openalex.org/S4363608312","display_name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","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/A5062232960","display_name":"Yangyan Deng","orcid":"https://orcid.org/0009-0008-9704-2157"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangyan Deng","raw_affiliation_strings":["Beihang University,school of Astronautics,Beijing,China","school of Astronautics, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,school of Astronautics,Beijing,China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"school of Astronautics, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014038368","display_name":"Ding Yuan","orcid":"https://orcid.org/0000-0002-6184-6371"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ding Yuan","raw_affiliation_strings":["Beihang University,school of Astronautics,Beijing,China","school of Astronautics, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,school of Astronautics,Beijing,China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"school of Astronautics, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100430288","display_name":"Hong Zhang","orcid":"https://orcid.org/0009-0007-9940-4046"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Zhang","raw_affiliation_strings":["Beihang University,school of Astronautics,Beijing,China","school of Astronautics, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University,school of Astronautics,Beijing,China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"school of Astronautics, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09845815,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"528","last_page":"533"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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":0.9998999834060669,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9965000152587891,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9926000237464905,"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/consistency","display_name":"Consistency (knowledge bases)","score":0.7380843162536621},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7342100143432617},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"Adaptive sampling","score":0.7032868266105652},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6481897830963135},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6134902834892273},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5652806758880615},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5587719082832336},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.5180249810218811},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5105810761451721},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.45579206943511963},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4509349763393402},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3538999557495117},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3272671699523926},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19556167721748352},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10183271765708923}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7380843162536621},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7342100143432617},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.7032868266105652},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6481897830963135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6134902834892273},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5652806758880615},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5587719082832336},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.5180249810218811},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5105810761451721},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.45579206943511963},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4509349763393402},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3538999557495117},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3272671699523926},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19556167721748352},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10183271765708923},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rcar54675.2022.9872231","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rcar54675.2022.9872231","pdf_url":null,"source":{"id":"https://openalex.org/S4363608312","display_name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Real-time Computing and Robotics (RCAR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1964057156","https://openalex.org/W2008706659","https://openalex.org/W2205172244","https://openalex.org/W2926429807","https://openalex.org/W2962793285","https://openalex.org/W2982169158","https://openalex.org/W2982809261","https://openalex.org/W2985775862","https://openalex.org/W2992718396","https://openalex.org/W3034375692","https://openalex.org/W3034524082","https://openalex.org/W3034530552","https://openalex.org/W3034564916","https://openalex.org/W3034600477","https://openalex.org/W3035483468","https://openalex.org/W3042904022","https://openalex.org/W3107389224","https://openalex.org/W3159272845","https://openalex.org/W3170262190","https://openalex.org/W3170748769","https://openalex.org/W3193766563","https://openalex.org/W3204267695","https://openalex.org/W6688032157","https://openalex.org/W6780948282","https://openalex.org/W6794617226"],"related_works":["https://openalex.org/W2038693912","https://openalex.org/W1991602789","https://openalex.org/W1582396021","https://openalex.org/W1988359706","https://openalex.org/W312558119","https://openalex.org/W4210985407","https://openalex.org/W2335441444","https://openalex.org/W138014004","https://openalex.org/W2075598034","https://openalex.org/W2984441180"],"abstract_inverted_index":{"With":[0],"the":[1,15,43,83,102,113,118,121,125,131,138,148,156,168,173,180,186,203],"development":[2],"of":[3,45,89,133,175],"deep":[4],"learning,":[5],"multi-view":[6,34],"stereo":[7,35],"has":[8,198],"achieved":[9],"significant":[10],"progress":[11],"recently.":[12],"Due":[13],"to":[14,38,146,202],"expensive":[16],"three-dimension":[17],"supervision,":[18],"self-supervised":[19,30,195],"methods":[20],"have":[21],"more":[22],"potential.":[23],"In":[24,100],"this":[25,63,87,98],"work,":[26],"a":[27,91],"novel":[28],"two-stage":[29,92,178],"learning":[31,196],"framework":[32,197],"for":[33],"is":[36,80,94,164],"proposed":[37,177],"overcome":[39,147],"photometric":[40,149],"dependency":[41],"and":[42,107,116,161],"effect":[44],"foreshortening.":[46],"On":[47],"considering":[48],"that":[49,193],"accurate":[50],"depth":[51,60,70,105,126,159],"hypothesis":[52],"always":[53],"plays":[54],"an":[55,68],"important":[56],"role":[57],"in":[58,97,112,120,167],"estimating":[59],"information.":[61],"Therefore,":[62],"work":[64],"concentrates":[65],"on":[66,74,185],"designing":[67],"adaptive":[69],"sampling":[71,127],"module":[72,128],"based":[73],"neighboring":[75],"spatial":[76],"patches":[77],"propagation,":[78],"which":[79],"determined":[81],"by":[82,129,152],"normal":[84,108,162],"maps.":[85],"From":[86],"point":[88],"view,":[90],"process":[93],"carried":[95,183],"out":[96,184],"work.":[99],"detail,":[101],"coarse":[103],"initial":[104],"maps":[106,109,160,163],"are":[110,141,182],"obtained":[111],"first":[114],"stage,":[115],"then":[117],"network":[119],"second":[122],"stage":[123],"refines":[124],"taking":[130],"influence":[132],"foreshortening":[134],"into":[135],"account.":[136],"Furthermore,":[137],"loss":[139,169],"functions":[140],"developed":[142],"including":[143],"feature-metric":[144],"consistency":[145,157],"inconsistency":[150],"caused":[151],"lighting":[153],"variation.":[154],"Moreover,":[155],"between":[158],"also":[165],"employed":[166],"functions.":[170],"To":[171],"evaluate":[172],"effectiveness":[174],"our":[176,194],"framework,":[179],"experiments":[181],"DTU":[187],"datasets.":[188],"The":[189],"experimental":[190],"results":[191],"demonstrate":[192],"excellent":[199],"performance":[200],"compared":[201],"baseline":[204],"methods.":[205]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
