{"id":"https://openalex.org/W3157032163","doi":"https://doi.org/10.1109/access.2021.3076346","title":"Monocular Depth Estimation Based on Multi-Scale Depth Map Fusion","display_name":"Monocular Depth Estimation Based on Multi-Scale Depth Map Fusion","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3157032163","doi":"https://doi.org/10.1109/access.2021.3076346","mag":"3157032163"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3076346","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3076346","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09417196.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09417196.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035732957","display_name":"Yang Xin","orcid":"https://orcid.org/0000-0002-8939-8590"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Yang","raw_affiliation_strings":["China-Germany Artificial Intelligence Institute (Jiangmen), Jiangmen, China","Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China"],"affiliations":[{"raw_affiliation_string":"China-Germany Artificial Intelligence Institute (Jiangmen), Jiangmen, China","institution_ids":["https://openalex.org/I4210100255"]},{"raw_affiliation_string":"Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China","institution_ids":["https://openalex.org/I4210151615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021360968","display_name":"Qingling Chang","orcid":"https://orcid.org/0000-0002-1937-1165"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingling Chang","raw_affiliation_strings":["China-Germany Artificial Intelligence Institute (Jiangmen), Jiangmen, China","Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China"],"affiliations":[{"raw_affiliation_string":"China-Germany Artificial Intelligence Institute (Jiangmen), Jiangmen, China","institution_ids":["https://openalex.org/I4210100255"]},{"raw_affiliation_string":"Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China","institution_ids":["https://openalex.org/I4210151615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054505709","display_name":"Xinglin Liu","orcid":"https://orcid.org/0000-0001-7503-4211"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinglin Liu","raw_affiliation_strings":["China-Germany Artificial Intelligence Institute (Jiangmen), Jiangmen, China","Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China"],"affiliations":[{"raw_affiliation_string":"China-Germany Artificial Intelligence Institute (Jiangmen), Jiangmen, China","institution_ids":["https://openalex.org/I4210100255"]},{"raw_affiliation_string":"Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China","institution_ids":["https://openalex.org/I4210151615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086080821","display_name":"Siyuan He","orcid":"https://orcid.org/0000-0001-8072-9632"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyuan He","raw_affiliation_strings":["China-Germany Artificial Intelligence Institute (Jiangmen), Jiangmen, China","Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China"],"affiliations":[{"raw_affiliation_string":"China-Germany Artificial Intelligence Institute (Jiangmen), Jiangmen, China","institution_ids":["https://openalex.org/I4210100255"]},{"raw_affiliation_string":"Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China","institution_ids":["https://openalex.org/I4210151615"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100783114","display_name":"Yan Cui","orcid":"https://orcid.org/0000-0001-5324-092X"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210151615","display_name":"Wuyi University","ror":"https://ror.org/0488wz367","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210151615"]},{"id":"https://openalex.org/I4210165204","display_name":"Zhuhai Institute of Advanced Technology","ror":"https://ror.org/05r1mzq61","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761","https://openalex.org/I4210165204"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Cui","raw_affiliation_strings":["China-Germany Artificial Intelligence Institute (Jiangmen), Jiangmen, China","Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China","Zhuhai 4Dage Network Technology, Zhuhai, China"],"affiliations":[{"raw_affiliation_string":"China-Germany Artificial Intelligence Institute (Jiangmen), Jiangmen, China","institution_ids":["https://openalex.org/I4210100255"]},{"raw_affiliation_string":"Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China","institution_ids":["https://openalex.org/I4210151615"]},{"raw_affiliation_string":"Zhuhai 4Dage Network Technology, Zhuhai, China","institution_ids":["https://openalex.org/I4210165204"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5035732957"],"corresponding_institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210151615"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.872,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.75213925,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"9","issue":null,"first_page":"67696","last_page":"67705"},"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":0.9980999827384949,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9897000193595886,"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/depth-map","display_name":"Depth map","score":0.7652181386947632},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7290729880332947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7222381830215454},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6290814876556396},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5605679154396057},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.5524998307228088},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5519471168518066},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5064371824264526},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5037316679954529},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4932214617729187},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4139983355998993},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39109861850738525},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12229090929031372},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10631012916564941},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09813472628593445},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09507596492767334}],"concepts":[{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.7652181386947632},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7290729880332947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7222381830215454},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6290814876556396},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5605679154396057},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.5524998307228088},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5519471168518066},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5064371824264526},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5037316679954529},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4932214617729187},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4139983355998993},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39109861850738525},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12229090929031372},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10631012916564941},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09813472628593445},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09507596492767334},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3076346","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3076346","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09417196.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:33b45444e662415c828e1bb909e018c8","is_oa":true,"landing_page_url":"https://doaj.org/article/33b45444e662415c828e1bb909e018c8","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 67696-67705 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3076346","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3076346","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09417196.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3060454441","display_name":null,"funder_award_id":"2019AL032","funder_id":"https://openalex.org/F4320324310","funder_display_name":"Wuyi University"}],"funders":[{"id":"https://openalex.org/F4320324310","display_name":"Wuyi University","ror":"https://ror.org/059djzq42"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3157032163.pdf","grobid_xml":"https://content.openalex.org/works/W3157032163.grobid-xml"},"referenced_works_count":60,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1803059841","https://openalex.org/W1817277359","https://openalex.org/W1901129140","https://openalex.org/W1905829557","https://openalex.org/W1923184257","https://openalex.org/W1976514650","https://openalex.org/W1985238052","https://openalex.org/W2108598243","https://openalex.org/W2109255472","https://openalex.org/W2125416623","https://openalex.org/W2171740948","https://openalex.org/W2300779272","https://openalex.org/W2397854647","https://openalex.org/W2520707372","https://openalex.org/W2560023338","https://openalex.org/W2605938684","https://openalex.org/W2609883120","https://openalex.org/W2752782242","https://openalex.org/W2796048785","https://openalex.org/W2798441115","https://openalex.org/W2798727000","https://openalex.org/W2798927139","https://openalex.org/W2803168974","https://openalex.org/W2907670226","https://openalex.org/W2911826324","https://openalex.org/W2951234442","https://openalex.org/W2962741876","https://openalex.org/W2962807621","https://openalex.org/W2963045776","https://openalex.org/W2963420686","https://openalex.org/W2963488291","https://openalex.org/W2963591054","https://openalex.org/W2963911235","https://openalex.org/W2967115342","https://openalex.org/W2973188935","https://openalex.org/W2982014906","https://openalex.org/W2985775862","https://openalex.org/W2991089415","https://openalex.org/W2999251606","https://openalex.org/W3015606539","https://openalex.org/W3025697288","https://openalex.org/W3038274920","https://openalex.org/W3080081801","https://openalex.org/W3087828854","https://openalex.org/W3088365851","https://openalex.org/W3120644635","https://openalex.org/W3173727695","https://openalex.org/W4288111771","https://openalex.org/W4289082871","https://openalex.org/W6605121731","https://openalex.org/W6638480814","https://openalex.org/W6639824700","https://openalex.org/W6685261749","https://openalex.org/W6757246177","https://openalex.org/W6758554110","https://openalex.org/W6768100795","https://openalex.org/W6771062828","https://openalex.org/W6778038363","https://openalex.org/W6786385858"],"related_works":["https://openalex.org/W3000097931","https://openalex.org/W2354322770","https://openalex.org/W4237547500","https://openalex.org/W1570848052","https://openalex.org/W3205445068","https://openalex.org/W3134004915","https://openalex.org/W4328027016","https://openalex.org/W3210711677","https://openalex.org/W4200218943","https://openalex.org/W3111845905"],"abstract_inverted_index":{"Monocular":[0],"depth":[1,17,25,68,135,141,153,163,169,176,182,185,197,204,223],"estimation":[2,18,26],"is":[3,52,85],"a":[4,31,41,80,108,115],"basic":[5],"task":[6],"in":[7,55,79,89,160,249],"machine":[8],"vision.":[9],"In":[10],"recent":[11],"years,":[12],"the":[13,56,66,92,126,146,161,218,253],"performance":[14],"of":[15,44,49,94,97,129],"monocular":[16],"has":[19],"been":[20],"greatly":[21],"improved.":[22],"However,":[23],"most":[24],"networks":[27],"are":[28,99],"based":[29],"on":[30,172,252],"very":[32],"deep":[33],"network":[34,112,148],"to":[35,40,65,118,124,149,156],"extract":[36],"features":[37],"that":[38,113,199,217],"lead":[39],"large":[42],"amount":[43],"information":[45,51,62,98,133,159,205,228],"lost.":[46],"The":[47],"loss":[48,63,96],"object":[50,71,131,158,210,227],"particularly":[53,100],"serious":[54],"encoding":[57],"and":[58,74,134,212,232],"decoding":[59],"process.":[60],"This":[61],"leads":[64],"estimated":[67],"maps":[69,154,170,186,198,224],"lacking":[70],"structure":[72,213],"detail":[73],"have":[75,187,208],"non-clear":[76],"edges.":[77],"Especially":[78],"complex":[81],"indoor":[82],"environment,":[83],"which":[84,144],"our":[86,175,233,245],"research":[87],"focus":[88],"this":[90,95,104],"paper,":[91],"consequences":[93],"serious.":[101],"To":[102],"solve":[103],"problem,":[105],"we":[106,137,194],"propose":[107,138],"Dense":[109],"feature":[110,116],"fusion":[111,127,142,147],"uses":[114],"pyramid":[117],"aggregate":[119],"various":[120,151],"scale":[121,152],"features.":[122],"Furthermore,":[123,239],"improve":[125],"effectiveness":[128],"decoded":[130],"contour":[132,211],"information,":[136],"an":[139],"adaptive":[140],"module,":[143],"allows":[145],"fuse":[150],"adaptively":[155],"increase":[157],"predicted":[162,178],"map.":[164],"Unlike":[165],"other":[166,230,242],"work":[167],"predicting":[168],"relying":[171],"U-NET":[173],"architecture,":[174],"map":[177],"by":[179],"fusing":[180,192],"multi-scale":[181],"maps.":[183],"These":[184],"their":[188],"own":[189],"characteristics.":[190],"By":[191],"them,":[193],"can":[195,221],"estimate":[196],"not":[200],"only":[201],"include":[202],"accurate":[203],"but":[206],"also":[207,235],"rich":[209],"detail.":[214],"Experiments":[215],"indicate":[216],"proposed":[219],"model":[220,234],"predict":[222],"with":[225,241],"more":[226],"than":[229],"prework,":[231],"shows":[236],"competitive":[237],"accuracy.":[238],"compared":[240],"contemporary":[243],"techniques,":[244],"method":[246],"gets":[247],"state-of-the-art":[248],"edge":[250],"accuracy":[251],"NYU":[254],"Depth":[255],"V2":[256],"dataset.":[257]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}