{"id":"https://openalex.org/W3161752280","doi":"https://doi.org/10.1109/icpr48806.2021.9413264","title":"Dynamic Guided Network for Monocular Depth Estimation","display_name":"Dynamic Guided Network for Monocular Depth Estimation","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3161752280","doi":"https://doi.org/10.1109/icpr48806.2021.9413264","mag":"3161752280"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9413264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9413264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5023685407","display_name":"Xiaoxia Xing","orcid":"https://orcid.org/0000-0002-1680-093X"},"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":"Xiaoxia Xing","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/A5103021731","display_name":"Yinghao Cai","orcid":"https://orcid.org/0000-0003-3024-2943"},"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/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinghao Cai","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006041868","display_name":"Yanqing Wang","orcid":"https://orcid.org/0000-0002-5961-0482"},"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/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanqing Wang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089404454","display_name":"Tao L\u00fc","orcid":"https://orcid.org/0000-0001-8117-2012"},"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/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Lu","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103134845","display_name":"Yiping Yang","orcid":"https://orcid.org/0000-0003-4426-2283"},"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/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiping Yang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088324062","display_name":"Dayong Wen","orcid":null},"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/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dayong Wen","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"5459","last_page":"5465"},"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":0.9973000288009644,"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":0.9959999918937683,"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/upsampling","display_name":"Upsampling","score":0.9318159222602844},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7884259223937988},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.732701301574707},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6965105533599854},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6401952505111694},{"id":"https://openalex.org/keywords/depth-map","display_name":"Depth map","score":0.5879724025726318},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5785888433456421},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5259121656417847},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5218122005462646},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5104257464408875},{"id":"https://openalex.org/keywords/high-dynamic-range","display_name":"High dynamic range","score":0.4848881661891937},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4724327027797699},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42456015944480896},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.42134952545166016},{"id":"https://openalex.org/keywords/dynamic-range","display_name":"Dynamic range","score":0.3621594309806824},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29825443029403687},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11732065677642822}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.9318159222602844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7884259223937988},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.732701301574707},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6965105533599854},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6401952505111694},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.5879724025726318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5785888433456421},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5259121656417847},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5218122005462646},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5104257464408875},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.4848881661891937},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4724327027797699},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42456015944480896},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.42134952545166016},{"id":"https://openalex.org/C87133666","wikidata":"https://www.wikidata.org/wiki/Q1161699","display_name":"Dynamic range","level":2,"score":0.3621594309806824},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29825443029403687},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11732065677642822},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9413264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9413264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G398002619","display_name":null,"funder_award_id":"U1913201","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1533861849","https://openalex.org/W1818727054","https://openalex.org/W1901129140","https://openalex.org/W2097261533","https://openalex.org/W2104599718","https://openalex.org/W2104600947","https://openalex.org/W2108598243","https://openalex.org/W2145567954","https://openalex.org/W2160956336","https://openalex.org/W2164517370","https://openalex.org/W2171740948","https://openalex.org/W2194775991","https://openalex.org/W2414711238","https://openalex.org/W2563100679","https://openalex.org/W2587989515","https://openalex.org/W2606794968","https://openalex.org/W2630837129","https://openalex.org/W2769945355","https://openalex.org/W2795321555","https://openalex.org/W2798664922","https://openalex.org/W2907670226","https://openalex.org/W2951234442","https://openalex.org/W2953133772","https://openalex.org/W2955058313","https://openalex.org/W2963091558","https://openalex.org/W2963488291","https://openalex.org/W2963591054","https://openalex.org/W2963881378","https://openalex.org/W2963911235","https://openalex.org/W2964193874","https://openalex.org/W2965376383","https://openalex.org/W2993235622","https://openalex.org/W3009020965","https://openalex.org/W3110653837","https://openalex.org/W3120644635","https://openalex.org/W4241716071","https://openalex.org/W4289082871","https://openalex.org/W6605121731","https://openalex.org/W6631943919","https://openalex.org/W6639824700","https://openalex.org/W6681423220","https://openalex.org/W6685261749","https://openalex.org/W6716109767","https://openalex.org/W6733387591"],"related_works":["https://openalex.org/W2795471480","https://openalex.org/W2104324080","https://openalex.org/W2520322935","https://openalex.org/W3005941135","https://openalex.org/W2086087387","https://openalex.org/W2027589961","https://openalex.org/W2140069086","https://openalex.org/W2884377208","https://openalex.org/W2155505427","https://openalex.org/W2525745698"],"abstract_inverted_index":{"Self-attention":[0],"and":[1,125],"encoder-decoder":[2,45],"have":[3],"been":[4],"widely":[5],"used":[6],"in":[7],"the":[8,27,38,44,61,83,88,109,112],"deep":[9],"neural":[10],"network":[11],"for":[12],"monocular":[13],"depth":[14,85,114,129],"estimation.":[15],"The":[16],"self-attention":[17],"mechanism":[18],"is":[19],"capable":[20],"of":[21,29,37,63,111],"capturing":[22],"long-range":[23],"dependencies":[24],"by":[25,33,51,74],"computing":[26],"representation":[28],"each":[30],"image":[31],"position":[32],"a":[34,93],"weighted":[35],"sum":[36],"features":[39,106],"at":[40],"all":[41],"positions,":[42],"while":[43],"can":[46],"capture":[47],"detailed":[48],"structural":[49],"information":[50],"gradually":[52],"recovering":[53],"spatial":[54],"information.":[55],"In":[56,87],"this":[57],"work,":[58],"we":[59,91],"combine":[60],"advantages":[62],"both":[64],"methods.":[65],"Specifically,":[66],"our":[67,120],"proposed":[68],"model,":[69],"DGNet,":[70],"extends":[71],"EMANet":[72],"[1]":[73],"adding":[75],"an":[76],"effective":[77],"decoder":[78,89],"module":[79,97],"to":[80,107],"progressively":[81],"refine":[82],"coarse":[84,113],"map.":[86,115],"stage,":[90],"design":[92],"dynamic":[94],"guided":[95],"upsampling":[96,110],"that":[98,119],"employs":[99],"dynamically":[100],"generated":[101],"kernel":[102],"conditioned":[103],"on":[104],"low-level":[105],"guide":[108],"Experimental":[116],"results":[117],"demonstrate":[118],"method":[121],"obtains":[122],"higher":[123],"accuracy":[124],"generates":[126],"visually":[127],"pleasant":[128],"maps.":[130]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}