{"id":"https://openalex.org/W3110653837","doi":"https://doi.org/10.1109/tip.2020.3040528","title":"Learning Guided Convolutional Network for Depth Completion","display_name":"Learning Guided Convolutional Network for Depth Completion","publication_year":2020,"publication_date":"2020-12-09","ids":{"openalex":"https://openalex.org/W3110653837","doi":"https://doi.org/10.1109/tip.2020.3040528","mag":"3110653837","pmid":"https://pubmed.ncbi.nlm.nih.gov/33290217"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2020.3040528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.3040528","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","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/A5101733791","display_name":"Jie Tang","orcid":"https://orcid.org/0000-0001-5556-2084"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Tang","raw_affiliation_strings":["College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-5556-2084","affiliations":[{"raw_affiliation_string":"College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080707476","display_name":"Fei-Peng Tian","orcid":"https://orcid.org/0000-0001-8105-5836"},"institutions":[{"id":"https://openalex.org/I2800287464","display_name":"State Administration of Cultural Heritage","ror":"https://ror.org/04d0vc473","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800287464"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei-Peng Tian","raw_affiliation_strings":["Key Research Center for Surface Monitoring and Analysis of Cultural Relics (SMARC), State Administration of Cultural Heritage, Beijing, China","School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-8105-5836","affiliations":[{"raw_affiliation_string":"Key Research Center for Surface Monitoring and Analysis of Cultural Relics (SMARC), State Administration of Cultural Heritage, Beijing, China","institution_ids":["https://openalex.org/I2800287464"]},{"raw_affiliation_string":"School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100721881","display_name":"Wei Feng","orcid":"https://orcid.org/0000-0003-3809-1086"},"institutions":[{"id":"https://openalex.org/I2800287464","display_name":"State Administration of Cultural Heritage","ror":"https://ror.org/04d0vc473","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800287464"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Feng","raw_affiliation_strings":["Key Research Center for Surface Monitoring and Analysis of Cultural Relics (SMARC), State Administration of Cultural Heritage, Beijing, China","School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-3809-1086","affiliations":[{"raw_affiliation_string":"Key Research Center for Surface Monitoring and Analysis of Cultural Relics (SMARC), State Administration of Cultural Heritage, Beijing, China","institution_ids":["https://openalex.org/I2800287464"]},{"raw_affiliation_string":"School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100402515","display_name":"Jian Li","orcid":"https://orcid.org/0000-0002-5749-2734"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Li","raw_affiliation_strings":["College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-5749-2734","affiliations":[{"raw_affiliation_string":"College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084953118","display_name":"Ping Tan","orcid":"https://orcid.org/0000-0002-4506-6973"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ping Tan","raw_affiliation_strings":["School of Computing Science, Simon Fraser University, Burnaby, BC, Canada"],"raw_orcid":"https://orcid.org/0000-0002-4506-6973","affiliations":[{"raw_affiliation_string":"School of Computing Science, Simon Fraser University, Burnaby, BC, Canada","institution_ids":["https://openalex.org/I18014758"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":15.1734,"has_fulltext":false,"cited_by_count":274,"citation_normalized_percentile":{"value":0.99329825,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"30","issue":null,"first_page":"1116","last_page":"1129"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9983999729156494,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9977999925613403,"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":0.7985836267471313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7293119430541992},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5833491683006287},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5580965280532837},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5222640633583069},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4996144771575928},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4920041263103485},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.48460114002227783},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4736422598361969},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.45107123255729675},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.442105770111084},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4314744770526886},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4200730621814728},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.11457589268684387}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7985836267471313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7293119430541992},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5833491683006287},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5580965280532837},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5222640633583069},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4996144771575928},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4920041263103485},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.48460114002227783},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4736422598361969},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.45107123255729675},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.442105770111084},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4314744770526886},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4200730621814728},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.11457589268684387},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2020.3040528","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2020.3040528","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:33290217","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33290217","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-124673","is_oa":false,"landing_page_url":"http://gateway.isiknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=LinksAMR&SrcApp=PARTNER_APP&DestLinkType=FullRecord&DestApp=WOS&KeyUT=000600285000002","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G3215501501","display_name":null,"funder_award_id":"61973311","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"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":88,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1484539719","https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W1872406745","https://openalex.org/W1918250297","https://openalex.org/W1923184257","https://openalex.org/W1967027087","https://openalex.org/W1985238052","https://openalex.org/W2005441409","https://openalex.org/W2030300879","https://openalex.org/W2035773017","https://openalex.org/W2093500899","https://openalex.org/W2099244020","https://openalex.org/W2104599718","https://openalex.org/W2104600947","https://openalex.org/W2104620097","https://openalex.org/W2117248802","https://openalex.org/W2118273112","https://openalex.org/W2125188192","https://openalex.org/W2128357735","https://openalex.org/W2136154655","https://openalex.org/W2144041313","https://openalex.org/W2153388956","https://openalex.org/W2160956336","https://openalex.org/W2164517370","https://openalex.org/W2194775991","https://openalex.org/W2195231623","https://openalex.org/W2199472553","https://openalex.org/W2214189948","https://openalex.org/W2231495490","https://openalex.org/W2397830550","https://openalex.org/W2397854647","https://openalex.org/W2414711238","https://openalex.org/W2440384215","https://openalex.org/W2494890720","https://openalex.org/W2512689497","https://openalex.org/W2520808298","https://openalex.org/W2601564443","https://openalex.org/W2606202972","https://openalex.org/W2612445135","https://openalex.org/W2735974062","https://openalex.org/W2794739174","https://openalex.org/W2805646839","https://openalex.org/W2885093229","https://openalex.org/W2886851716","https://openalex.org/W2895230054","https://openalex.org/W2899479761","https://openalex.org/W2908510526","https://openalex.org/W2949117887","https://openalex.org/W2953133772","https://openalex.org/W2961926014","https://openalex.org/W2963045776","https://openalex.org/W2963222130","https://openalex.org/W2963316641","https://openalex.org/W2963416674","https://openalex.org/W2963417597","https://openalex.org/W2963727650","https://openalex.org/W2963867516","https://openalex.org/W2964110533","https://openalex.org/W2964121744","https://openalex.org/W2964326562","https://openalex.org/W2968373168","https://openalex.org/W2969202876","https://openalex.org/W2980467688","https://openalex.org/W2986701260","https://openalex.org/W2992464978","https://openalex.org/W2998031326","https://openalex.org/W2998293366","https://openalex.org/W3009783082","https://openalex.org/W3125028070","https://openalex.org/W4241716071","https://openalex.org/W4297775537","https://openalex.org/W6605121731","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6678827375","https://openalex.org/W6689586722","https://openalex.org/W6716109767","https://openalex.org/W6723408449","https://openalex.org/W6725721286","https://openalex.org/W6726811299","https://openalex.org/W6737664043","https://openalex.org/W6749630058","https://openalex.org/W6751382148","https://openalex.org/W6753806659","https://openalex.org/W6754922683","https://openalex.org/W6757817989"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W4281783339","https://openalex.org/W1964041166","https://openalex.org/W4390887692","https://openalex.org/W4221065211"],"abstract_inverted_index":{"Dense":[0],"depth":[1,19,101,193],"perception":[2],"is":[3,22,37],"critical":[4],"for":[5,50,114,151,227],"autonomous":[6],"driving":[7],"and":[8,61,111,129,141,171,187,214],"other":[9],"robotics":[10],"applications.":[11],"However,":[12,53],"modern":[13],"LiDAR":[14,29,59],"sensors":[15],"only":[16],"provide":[17],"sparse":[18,28],"measurement.":[20],"It":[21,179,201],"thus":[23],"necessary":[24],"to":[25,40,84,98,124,138,154,163],"complete":[26],"the":[27,58,74,89,100,184,191,197],"data,":[30],"where":[31],"a":[32,80,135],"synchronized":[33],"guidance":[34,90],"RGB":[35,62],"image":[36,63,76,102],"often":[38,55],"used":[39],"facilitate":[41],"this":[42,51,105],"completion.":[43],"Many":[44],"neural":[45],"networks":[46],"have":[47],"been":[48],"designed":[49],"task.":[52],"they":[54],"na\u00efvely":[56],"fuse":[57],"data":[60],"information":[64],"by":[65,73],"performing":[66],"feature":[67,116,152],"concatenation":[68],"or":[69],"element-wise":[70],"addition.":[71],"Inspired":[72],"guided":[75,82],"filtering,":[77],"we":[78],"design":[79,134],"novel":[81],"network":[83,108],"predict":[85],"kernel":[86],"weights":[87],"from":[88],"image.":[91],"These":[92],"predicted":[93],"kernels":[94,113,121],"are":[95],"then":[96],"applied":[97],"extract":[99],"features.":[103],"In":[104],"way,":[106],"our":[107,165],"generates":[109],"content-dependent":[110],"spatially-variant":[112,120],"multi-modal":[115],"fusion.":[117],"Dynamically":[118],"generated":[119],"could":[122],"lead":[123],"prohibitive":[125],"GPU":[126,145],"memory":[127,142,146],"consumption":[128],"computation":[130,140],"overhead.":[131],"We":[132,159],"further":[133],"convolution":[136],"factorization":[137],"reduce":[139],"consumption.":[143],"The":[144,222],"reduction":[147],"makes":[148],"it":[149],"possible":[150],"fusion":[153],"work":[155],"in":[156],"multi-stage":[157],"scheme.":[158],"conduct":[160],"comprehensive":[161],"experiments":[162],"verify":[164],"method":[166,175],"on":[167,183,190],"real-world":[168],"outdoor,":[169],"indoor":[170],"synthetic":[172],"datasets.":[173],"Our":[174],"produces":[176],"strong":[177,204],"results.":[178],"outperforms":[180],"state-of-the-art":[181],"methods":[182],"NYUv2":[185],"dataset":[186],"ranks":[188],"1st":[189],"KITTI":[192],"completion":[194],"benchmark":[195],"at":[196],"time":[198],"of":[199],"submission.":[200],"also":[202],"presents":[203],"generalization":[205],"capability":[206],"under":[207],"different":[208],"3D":[209],"point":[210],"densities,":[211],"various":[212],"lighting":[213],"weather":[215],"conditions":[216],"as":[217,219],"well":[218],"cross-dataset":[220],"evaluations.":[221],"code":[223],"will":[224],"be":[225],"released":[226],"reproduction.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":47},{"year":2024,"cited_by_count":58},{"year":2023,"cited_by_count":48},{"year":2022,"cited_by_count":54},{"year":2021,"cited_by_count":40},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-16T09:24:06.705377","created_date":"2025-10-10T00:00:00"}