{"id":"https://openalex.org/W2792754932","doi":"https://doi.org/10.1109/spac.2017.8304283","title":"An effective single image depth estimating algorithm","display_name":"An effective single image depth estimating algorithm","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2792754932","doi":"https://doi.org/10.1109/spac.2017.8304283","mag":"2792754932"},"language":"en","primary_location":{"id":"doi:10.1109/spac.2017.8304283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spac.2017.8304283","pdf_url":null,"source":{"id":"https://openalex.org/S4306498208","display_name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","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":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","raw_type":"proceedings-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/A5036508065","display_name":"Baijiang Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baijiang Fan","raw_affiliation_strings":["School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049713946","display_name":"Yunbo Rao","orcid":"https://orcid.org/0000-0001-5433-7379"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunbo Rao","raw_affiliation_strings":["School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100431792","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0002-3865-8145"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102023998","display_name":"Jiali Song","orcid":"https://orcid.org/0000-0002-5309-6398"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiali Song","raw_affiliation_strings":["School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"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":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20487522,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5291","issue":null,"first_page":"242","last_page":"246"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9896000027656555,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7018918991088867},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7006680369377136},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6409705877304077},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5906528234481812},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5663766860961914},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5375807881355286},{"id":"https://openalex.org/keywords/depth-map","display_name":"Depth map","score":0.4991302490234375},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4689972400665283},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4535532593727112},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4307126998901367},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3889421224594116},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35492268204689026}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7018918991088867},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7006680369377136},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6409705877304077},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5906528234481812},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5663766860961914},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5375807881355286},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.4991302490234375},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4689972400665283},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4535532593727112},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4307126998901367},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3889421224594116},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35492268204689026}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/spac.2017.8304283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spac.2017.8304283","pdf_url":null,"source":{"id":"https://openalex.org/S4306498208","display_name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","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":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1445015017","https://openalex.org/W1494085959","https://openalex.org/W1803059841","https://openalex.org/W1905829557","https://openalex.org/W1976948919","https://openalex.org/W2026203852","https://openalex.org/W2044880603","https://openalex.org/W2083047701","https://openalex.org/W2158211626","https://openalex.org/W2163605009","https://openalex.org/W2171740948","https://openalex.org/W2243400293","https://openalex.org/W2298605637","https://openalex.org/W2336968928","https://openalex.org/W2519721163","https://openalex.org/W2752749650","https://openalex.org/W2951234442","https://openalex.org/W2963173190","https://openalex.org/W6639633739","https://openalex.org/W6683067110","https://openalex.org/W6684191040","https://openalex.org/W6685261749","https://openalex.org/W6697869303","https://openalex.org/W6990255718","https://openalex.org/W7058367366"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W4312417841","https://openalex.org/W4210874298","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Depth":[0],"estimating":[1,51,86],"from":[2,19,26,68],"image":[3,21,29,35,49,71],"is":[4,30],"a":[5,27,47,69],"essentially":[6],"important":[7],"work":[8],"in":[9],"many":[10],"situations.":[11],"However,":[12],"traditional":[13],"methods":[14,107],"always":[15],"extract":[16],"depth":[17,24,50,66],"information":[18,25],"binocular":[20],"pairs.":[22],"Estimating":[23],"single":[28,34,48,70],"much":[31],"harder":[32],"because":[33],"lake":[36],"the":[37,54,65,94,109,116],"relationship":[38],"between":[39],"global":[40],"and":[41,75,87,111],"local":[42],"coordinate.":[43],"This":[44],"paper":[45],"proposes":[46],"method":[52,61,80,95,104],"by":[53],"segmentation":[55],"convolutional":[56],"neural":[57],"network":[58],"method.":[59],"Our":[60],"aimed":[62],"at":[63],"getting":[64],"map":[67],"with":[72,105],"high":[73,76,88,98],"revolution":[74,89],"speed.":[77],"The":[78],"proposed":[79],"include":[81],"three":[82],"components:":[83],"segmentation,":[84],"coarse":[85],"refine.":[90],"Experiment":[91],"results":[92],"show":[93,115],"can":[96],"get":[97],"quality":[99],"results.":[100],"We":[101],"compare":[102],"our":[103],"other":[106],"on":[108],"accuracy":[110],"processing":[112],"time":[113],"to":[114],"advantages.":[117]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
