{"id":"https://openalex.org/W2793404847","doi":"https://doi.org/10.1109/tnnls.2017.2787781","title":"Collaborative Deconvolutional Neural Networks for Joint Depth Estimation and Semantic Segmentation","display_name":"Collaborative Deconvolutional Neural Networks for Joint Depth Estimation and Semantic Segmentation","publication_year":2018,"publication_date":"2018-03-20","ids":{"openalex":"https://openalex.org/W2793404847","doi":"https://doi.org/10.1109/tnnls.2017.2787781","mag":"2793404847","pmid":"https://pubmed.ncbi.nlm.nih.gov/29994159"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2017.2787781","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2787781","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5108392430","display_name":"Jing Liu","orcid":"https://orcid.org/0000-0003-0903-9131"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Liu","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0903-9131","affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100449563","display_name":"Yuhang Wang","orcid":"https://orcid.org/0000-0001-8871-6713"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhang Wang","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100355406","display_name":"Yong Li","orcid":"https://orcid.org/0000-0002-6521-5921"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101758238","display_name":"Jun Fu","orcid":"https://orcid.org/0000-0001-5734-7134"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Fu","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074215202","display_name":"Jiangyun Li","orcid":"https://orcid.org/0000-0003-2288-7901"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangyun Li","raw_affiliation_strings":["University of Science and Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology, Beijing, China","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100511737","display_name":"Hanqing Lu","orcid":"https://orcid.org/0000-0001-9506-3407"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanqing Lu","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1213,"has_fulltext":false,"cited_by_count":65,"citation_normalized_percentile":{"value":0.94014999,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"29","issue":"11","first_page":"5655","last_page":"5666"},"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":0.9994000196456909,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9961000084877014,"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/computer-science","display_name":"Computer science","score":0.7743585109710693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6723152995109558},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6275337934494019},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.6158193349838257},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5038575530052185},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.4891048073768616},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4418129324913025},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4366079568862915},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4220767617225647},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32150471210479736},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10279971361160278}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7743585109710693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6723152995109558},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6275337934494019},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.6158193349838257},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5038575530052185},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.4891048073768616},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4418129324913025},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4366079568862915},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4220767617225647},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32150471210479736},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10279971361160278},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2017.2787781","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2017.2787781","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:29994159","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29994159","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1997794202","display_name":"\u57fa\u4e8e\u76ee\u6807\u8bed\u4e49\u7684\u7f51\u7edc\u56fe\u50cf\u68c0\u7d22\u6280\u672f\u7814\u7a76","funder_award_id":"61472422","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G267313036","display_name":null,"funder_award_id":"61332016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"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":58,"referenced_works":["https://openalex.org/W78159342","https://openalex.org/W125693051","https://openalex.org/W1230023165","https://openalex.org/W1528789833","https://openalex.org/W1565402342","https://openalex.org/W1569892065","https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1803059841","https://openalex.org/W1836465849","https://openalex.org/W1849277567","https://openalex.org/W1903029394","https://openalex.org/W1905829557","https://openalex.org/W1910657905","https://openalex.org/W1915250530","https://openalex.org/W1923184257","https://openalex.org/W1923697677","https://openalex.org/W1969366022","https://openalex.org/W1992178727","https://openalex.org/W2026203852","https://openalex.org/W2066813062","https://openalex.org/W2067912884","https://openalex.org/W2074254947","https://openalex.org/W2083047701","https://openalex.org/W2103328396","https://openalex.org/W2103359735","https://openalex.org/W2104657103","https://openalex.org/W2124592697","https://openalex.org/W2125416623","https://openalex.org/W2125849446","https://openalex.org/W2132947399","https://openalex.org/W2139905387","https://openalex.org/W2141200610","https://openalex.org/W2147800946","https://openalex.org/W2158211626","https://openalex.org/W2158305599","https://openalex.org/W2158427031","https://openalex.org/W2171740948","https://openalex.org/W2194775991","https://openalex.org/W2221101993","https://openalex.org/W2343077198","https://openalex.org/W2354576866","https://openalex.org/W2949650786","https://openalex.org/W2950094539","https://openalex.org/W2951234442","https://openalex.org/W2962741876","https://openalex.org/W2962851944","https://openalex.org/W2963108253","https://openalex.org/W2963563573","https://openalex.org/W4300126339","https://openalex.org/W6603109438","https://openalex.org/W6605121731","https://openalex.org/W6631412525","https://openalex.org/W6638667902","https://openalex.org/W6639204139","https://openalex.org/W6666899075","https://openalex.org/W6683067110","https://openalex.org/W6685261749"],"related_works":["https://openalex.org/W143502885","https://openalex.org/W42113618","https://openalex.org/W2103468410","https://openalex.org/W2480115405","https://openalex.org/W3197542402","https://openalex.org/W1856228368","https://openalex.org/W2971527398","https://openalex.org/W1929207905","https://openalex.org/W4301042974","https://openalex.org/W3112772842"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1,119,251],"and":[2,17,23,71,95,98,120,130,138,175,211,227,243,252],"single-view":[3],"depth":[4,96,121,131,152,169,212,253],"estimation":[5,153,254],"are":[6,24,72,84,107,213],"two":[7,45,54,82,110,221,239],"fundamental":[8],"problems":[9,46],"in":[10,27,133],"computer":[11],"vision.":[12],"They":[13],"exploit":[14],"the":[15,93,104,128,167,176,197,203,249],"semantic":[16,94,118,129,200,250],"geometric":[18],"properties":[19],"of":[20,53,56,199,206,241],"images,":[21],"respectively,":[22],"thus":[25],"complementary":[26],"scene":[28],"understanding.":[29],"In":[30,123],"this":[31,124],"paper,":[32],"we":[33,126,150],"propose":[34],"a":[35,66,87,134,155,159,183],"collaborative":[36],"deconvolutional":[37],"neural":[38],"network":[39,137,148],"(C-DCNN)":[40],"to":[41,114,142,165,194],"jointly":[42,139,214],"model":[43],"these":[44,81,238],"for":[47,60,117],"mutual":[48],"promotion.":[49],"The":[50,63,77],"C-DCNN":[51],"consists":[52],"DCNNs,":[55],"which":[57,91],"each":[58,144],"is":[59,163,180,189,231],"one":[61],"task.":[62],"DCNNs":[64,83],"provide":[65],"finer":[67],"resolution":[68],"reconstruction":[69],"method":[70],"pretrained":[73],"with":[74],"hierarchical":[75],"supervision.":[76],"feature":[78],"maps":[79],"from":[80],"integrated":[85,105],"via":[86],"pointwise":[88],"bilinear":[89],"layer,":[90],"fuses":[92],"information":[97,242],"produces":[99],"higher":[100],"order":[101],"features.":[102],"Then,":[103],"features":[106,132],"fed":[108],"into":[109,171],"sibling":[111],"classification":[112,156],"layers":[113],"simultaneously":[115],"learn":[116],"estimation.":[122],"way,":[125],"combine":[127],"unified":[135],"deep":[136],"train":[140],"them":[141],"benefit":[143],"other.":[145],"Specifically,":[146],"during":[147],"training,":[149],"process":[151],"as":[154,192],"problem":[157],"where":[158,202],"soft":[160],"mapping":[161],"strategy":[162],"proposed":[164],"map":[166],"continuous":[168],"values":[170],"discrete":[172],"probability":[173],"distributions":[174],"cross":[177],"entropy":[178],"loss":[179],"used.":[181],"Besides,":[182],"fully":[184],"connected":[185],"conditional":[186],"random":[187],"field":[188],"also":[190],"used":[191],"postprocessing":[193],"further":[195],"improve":[196],"performance":[198],"segmentation,":[201],"proximity":[204],"relations":[205],"pixels":[207],"on":[208,220,247],"position,":[209],"intensity,":[210],"considered.":[215],"We":[216],"evaluate":[217],"our":[218,234],"approach":[219,235],"challenging":[222],"benchmarks:":[223],"NYU":[224],"Depth":[225],"V2":[226],"SUN":[228],"RGB-D.":[229],"It":[230],"demonstrated":[232],"that":[233],"effectively":[236],"utilizes":[237],"kinds":[240],"achieves":[244],"state-of-the-art":[245],"results":[246],"both":[248],"tasks.":[255]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
