{"id":"https://openalex.org/W2954432694","doi":"https://doi.org/10.1109/tits.2019.2913883","title":"Real-Time Semantic Segmentation-Based Stereo Reconstruction","display_name":"Real-Time Semantic Segmentation-Based Stereo Reconstruction","publication_year":2019,"publication_date":"2019-06-28","ids":{"openalex":"https://openalex.org/W2954432694","doi":"https://doi.org/10.1109/tits.2019.2913883","mag":"2954432694"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2019.2913883","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2913883","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","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/A5079231009","display_name":"Vlad\u2013Cristian Miclea","orcid":"https://orcid.org/0000-0002-5781-5433"},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Vlad-Cristian Miclea","raw_affiliation_strings":["Department of Computer Science, Technical University of Cluj-Napoca, Cluj-Napoca, Romania"],"raw_orcid":"https://orcid.org/0000-0002-5781-5433","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Technical University of Cluj-Napoca, Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I158333966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047954457","display_name":"Sergiu Nedevschi","orcid":"https://orcid.org/0000-0003-2018-4647"},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Sergiu Nedevschi","raw_affiliation_strings":["Department of Computer Science, Technical University of Cluj-Napoca, Cluj-Napoca, Romania"],"raw_orcid":"https://orcid.org/0000-0003-2018-4647","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Technical University of Cluj-Napoca, Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I158333966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I158333966"],"apc_list":null,"apc_paid":null,"fwci":2.0843,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.90031538,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"21","issue":"4","first_page":"1514","last_page":"1524"},"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T11569","display_name":"Optical Coherence Tomography Applications","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/computer-science","display_name":"Computer science","score":0.8066606521606445},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7662485241889954},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.6982382535934448},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.68342524766922},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.623249888420105},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6145349740982056},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6002247333526611},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.509110152721405},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3583546280860901},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1631704866886139}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8066606521606445},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7662485241889954},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6982382535934448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.68342524766922},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.623249888420105},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6145349740982056},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6002247333526611},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.509110152721405},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3583546280860901},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1631704866886139},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2019.2913883","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2913883","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G2044082748","display_name":null,"funder_award_id":"688652","funder_id":"https://openalex.org/F4320332999","funder_display_name":"Horizon 2020 Framework Programme"},{"id":"https://openalex.org/G984932415","display_name":null,"funder_award_id":"PN-III-P4-ID-PCE-2016-0727","funder_id":"https://openalex.org/F4320323983","funder_display_name":"Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii"}],"funders":[{"id":"https://openalex.org/F4320323983","display_name":"Unitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii","ror":"https://ror.org/01q7jq182"},{"id":"https://openalex.org/F4320332999","display_name":"Horizon 2020 Framework Programme","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W55377555","https://openalex.org/W63091017","https://openalex.org/W753012316","https://openalex.org/W1667652561","https://openalex.org/W1674866864","https://openalex.org/W1878947057","https://openalex.org/W1903029394","https://openalex.org/W1921093919","https://openalex.org/W1932937519","https://openalex.org/W1996126470","https://openalex.org/W2028365123","https://openalex.org/W2032339054","https://openalex.org/W2039548306","https://openalex.org/W2048679181","https://openalex.org/W2056072137","https://openalex.org/W2065533005","https://openalex.org/W2067681708","https://openalex.org/W2099244020","https://openalex.org/W2104853049","https://openalex.org/W2104974755","https://openalex.org/W2117248802","https://openalex.org/W2118810648","https://openalex.org/W2121781154","https://openalex.org/W2124109840","https://openalex.org/W2133255058","https://openalex.org/W2138089824","https://openalex.org/W2139900871","https://openalex.org/W2140836349","https://openalex.org/W2142926575","https://openalex.org/W2144041313","https://openalex.org/W2151646056","https://openalex.org/W2160956336","https://openalex.org/W2163883567","https://openalex.org/W2254462240","https://openalex.org/W2259424905","https://openalex.org/W2340897893","https://openalex.org/W2419448466","https://openalex.org/W2474236724","https://openalex.org/W2509033610","https://openalex.org/W2509391111","https://openalex.org/W2511611791","https://openalex.org/W2514653544","https://openalex.org/W2520808298","https://openalex.org/W2554232633","https://openalex.org/W2555147445","https://openalex.org/W2560023338","https://openalex.org/W2604231069","https://openalex.org/W2738441955","https://openalex.org/W2740797854","https://openalex.org/W2743353723","https://openalex.org/W2751625733","https://openalex.org/W2762439315","https://openalex.org/W2776033207","https://openalex.org/W2876993306","https://openalex.org/W3100388886","https://openalex.org/W4293406525","https://openalex.org/W4302296459","https://openalex.org/W6622239757","https://openalex.org/W6637151318","https://openalex.org/W6639138679","https://openalex.org/W6680601873","https://openalex.org/W6717372056","https://openalex.org/W6730092673","https://openalex.org/W6743438356","https://openalex.org/W7036195979"],"related_works":["https://openalex.org/W1981780420","https://openalex.org/W2182707996","https://openalex.org/W45233828","https://openalex.org/W2964988449","https://openalex.org/W188202134","https://openalex.org/W2397952901","https://openalex.org/W2029380707","https://openalex.org/W4255934811","https://openalex.org/W2465382974","https://openalex.org/W4388446985"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,51,81,96],"propose":[4,82,97],"a":[5,98],"novel":[6],"semantic":[7,48,72],"segmentation-based":[8],"stereo":[9,34,40],"reconstruction":[10],"method":[11],"that":[12,86],"can":[13,87],"keep":[14],"up":[15],"with":[16],"the":[17,20,32,39,75,90,118],"accuracy":[18],"of":[19],"state-of-the":[21],"art":[22],"approaches":[23],"while":[24],"running":[25],"in":[26,38],"real":[27],"time.":[28],"The":[29],"solution":[30],"follows":[31],"classic":[33],"pipeline,":[35],"each":[36,71],"step":[37],"workflow":[41],"being":[42],"enhanced":[43],"by":[44,60,70],"additional":[45,66],"information":[46,68],"from":[47],"segmentation.":[49,125],"Therefore,":[50],"introduce":[52],"several":[53],"improvements":[54],"to":[55,64],"computation,":[56],"aggregation,":[57],"and":[58,78],"optimization":[59,79],"adapting":[61],"existing":[62],"techniques":[63],"integrate":[65],"surface":[67],"given":[69],"class.":[73],"For":[74],"cost":[76],"computation":[77],"steps,":[80],"new":[83,99],"genetic":[84],"algorithms":[85],"incrementally":[88],"adjust":[89],"parameters":[91],"for":[92,113],"better":[93],"solutions.":[94],"Furthermore,":[95],"post-processing":[100],"edge-aware":[101],"filtering":[102],"technique":[103],"relying":[104],"on":[105],"an":[106],"improved":[107],"convolutional":[108],"neural":[109],"network":[110],"(CNN)":[111],"architecture":[112],"disparity":[114],"refinement.":[115],"We":[116],"obtain":[117],"competitive":[119],"results":[120],"at":[121],"30":[122],"frames/s,":[123],"including":[124]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}