{"id":"https://openalex.org/W4321192185","doi":"https://doi.org/10.1109/icce56470.2023.10043449","title":"Stereo Matching with Supplementary Boundary Information","display_name":"Stereo Matching with Supplementary Boundary Information","publication_year":2023,"publication_date":"2023-01-06","ids":{"openalex":"https://openalex.org/W4321192185","doi":"https://doi.org/10.1109/icce56470.2023.10043449"},"language":"en","primary_location":{"id":"doi:10.1109/icce56470.2023.10043449","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icce56470.2023.10043449","pdf_url":null,"source":{"id":"https://openalex.org/S4363607959","display_name":"2023 IEEE International Conference on Consumer Electronics (ICCE)","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":"2023 IEEE International Conference on Consumer Electronics (ICCE)","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/A5062335047","display_name":"Kaito Hashimoto","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kaito Hashimoto","raw_affiliation_strings":["Keio University,Department of Electronics and Electrical Engineering,Tokyo,Japan","Department of Electronics and Electrical Engineering, Keio University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Keio University,Department of Electronics and Electrical Engineering,Tokyo,Japan","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"Department of Electronics and Electrical Engineering, Keio University, Tokyo, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090181402","display_name":"Masaaki Ikehara","orcid":"https://orcid.org/0000-0003-3461-1507"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaaki Ikehara","raw_affiliation_strings":["Keio University,Department of Electronics and Electrical Engineering,Tokyo,Japan","Department of Electronics and Electrical Engineering, Keio University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Keio University,Department of Electronics and Electrical Engineering,Tokyo,Japan","institution_ids":["https://openalex.org/I203951103"]},{"raw_affiliation_string":"Department of Electronics and Electrical Engineering, Keio University, Tokyo, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01048185,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"05"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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":1.0,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9984999895095825,"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":0.9969000220298767,"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/ground-truth","display_name":"Ground truth","score":0.7621272802352905},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.6989271640777588},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6746873259544373},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.648766279220581},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5891082286834717},{"id":"https://openalex.org/keywords/gloss","display_name":"Gloss (optics)","score":0.5665581822395325},{"id":"https://openalex.org/keywords/occlusion","display_name":"Occlusion","score":0.5211582183837891},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4437176585197449},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3432621955871582},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3297961354255676}],"concepts":[{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.7621272802352905},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.6989271640777588},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6746873259544373},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.648766279220581},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5891082286834717},{"id":"https://openalex.org/C143025027","wikidata":"https://www.wikidata.org/wiki/Q900581","display_name":"Gloss (optics)","level":3,"score":0.5665581822395325},{"id":"https://openalex.org/C2776268601","wikidata":"https://www.wikidata.org/wiki/Q968808","display_name":"Occlusion","level":2,"score":0.5211582183837891},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4437176585197449},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3432621955871582},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3297961354255676},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2781448156","wikidata":"https://www.wikidata.org/wiki/Q1570182","display_name":"Coating","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce56470.2023.10043449","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icce56470.2023.10043449","pdf_url":null,"source":{"id":"https://openalex.org/S4363607959","display_name":"2023 IEEE International Conference on Consumer Electronics (ICCE)","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":"2023 IEEE International Conference on Consumer Electronics (ICCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1963629711","https://openalex.org/W1964057156","https://openalex.org/W2106813532","https://openalex.org/W2194775991","https://openalex.org/W2259424905","https://openalex.org/W2476548250","https://openalex.org/W2604231069","https://openalex.org/W2963446712","https://openalex.org/W2963619659","https://openalex.org/W3109908659","https://openalex.org/W4312871721"],"related_works":["https://openalex.org/W3119463769","https://openalex.org/W2035926194","https://openalex.org/W2514360315","https://openalex.org/W2045489541","https://openalex.org/W2040681928","https://openalex.org/W2134811186","https://openalex.org/W2160360150","https://openalex.org/W4247897165","https://openalex.org/W2358737221","https://openalex.org/W1985904311"],"abstract_inverted_index":{"Stereo":[0],"matching,":[1],"which":[2,35],"estimates":[3],"the":[4,52,57,64,68,99,104,117,124,131],"disparity":[5],"of":[6],"corresponding":[7,58,69],"points":[8,59],"in":[9],"paired":[10],"images,":[11],"has":[12],"problems":[13,79],"with":[14],"accuracy":[15,125],"degraded":[16],"by":[17,85,129],"occlusion,":[18,63],"repeated":[19,86],"texture,":[20],"texture-free":[21],"areas,":[22,89],"and":[23,54,108,112],"gloss.":[24,91],"To":[25],"address":[26],"this":[27],"problem,":[28],"we":[29,93],"focused":[30],"on":[31],"object":[32],"boundary":[33,72,100,118,133],"information,":[34],"is":[36,43,46,74,82],"less":[37],"susceptible":[38],"to":[39,49,62,77],"such":[40,78],"problems.":[41],"This":[42],"because":[44,80],"occlusion":[45],"more":[47],"likely":[48],"occur":[50],"at":[51],"boundaries,":[53],"even":[55],"if":[56],"disappear":[60],"due":[61],"boundaries":[65],"still":[66],"have":[67],"parts.":[70],"The":[71],"information":[73,134],"also":[75,121],"robust":[76],"it":[81],"not":[83],"affected":[84],"textures,":[87],"untextured":[88],"or":[90],"Therefore,":[92],"propose":[94,122],"a":[95,110,136],"method":[96],"for":[97,115],"generating":[98],"ground":[101,106],"truth":[102,107],"from":[103],"depth":[105],"develop":[109],"network":[111,138],"loss":[113],"function":[114],"estimating":[116],"information.":[119],"We":[120],"that":[123],"can":[126],"be":[127],"improved":[128],"incorporating":[130],"estimated":[132],"into":[135],"state-of-the-art":[137],"as":[139],"an":[140],"auxiliary.":[141]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
