{"id":"https://openalex.org/W4312280299","doi":"https://doi.org/10.1109/lgrs.2022.3222457","title":"Rethinking Monocular Height Estimation From a Classification Task Perspective Leveraging the Vision Transformer","display_name":"Rethinking Monocular Height Estimation From a Classification Task Perspective Leveraging the Vision Transformer","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312280299","doi":"https://doi.org/10.1109/lgrs.2022.3222457"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2022.3222457","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3222457","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5017083480","display_name":"Wenbo Sun","orcid":"https://orcid.org/0000-0002-7482-8981"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenbo Sun","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100341424","display_name":"Yichen Zhang","orcid":"https://orcid.org/0000-0003-4030-1572"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yichen Zhang","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","Hubei Luojia Laboratory, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"Hubei Luojia Laboratory, Wuhan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101998122","display_name":"Yifan Liao","orcid":"https://orcid.org/0000-0002-0493-771X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Liao","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036995131","display_name":"Biao Yang","orcid":"https://orcid.org/0000-0002-4434-0141"},"institutions":[{"id":"https://openalex.org/I4210113138","display_name":"Guangzhou Automobile Group (China)","ror":"https://ror.org/026fzn952","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210113138"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Biao Yang","raw_affiliation_strings":["Guangzhou Expressway Company, Ltd., Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangzhou Expressway Company, Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I4210113138"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072717490","display_name":"Mingchun Lin","orcid":"https://orcid.org/0000-0002-2587-0155"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mingchun Lin","raw_affiliation_strings":["Road and Bridge International Company, Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Road and Bridge International Company, Ltd., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006198920","display_name":"Ruifang Zhai","orcid":"https://orcid.org/0000-0001-5859-8971"},"institutions":[{"id":"https://openalex.org/I204823248","display_name":"Huazhong Agricultural University","ror":"https://ror.org/023b72294","country_code":"CN","type":"education","lineage":["https://openalex.org/I204823248"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruifang Zhai","raw_affiliation_strings":["Department of Computer Science, School of Informatics, Huazhong Agricultural University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, School of Informatics, Huazhong Agricultural University, Wuhan, China","institution_ids":["https://openalex.org/I204823248"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084683976","display_name":"Zhi Gao","orcid":"https://orcid.org/0000-0003-3325-1183"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Gao","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","Hubei Luojia Laboratory, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"Hubei Luojia Laboratory, Wuhan, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5017083480"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.8053,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.73344639,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9997000098228455,"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":0.9997000098228455,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bin","display_name":"Bin","score":0.7409208416938782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6518049836158752},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6257190704345703},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.613909900188446},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5028302073478699},{"id":"https://openalex.org/keywords/subdivision","display_name":"Subdivision","score":0.49390655755996704},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.47352027893066406},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.44399121403694153},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.44376638531684875},{"id":"https://openalex.org/keywords/discretization","display_name":"Discretization","score":0.43137529492378235},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4250544309616089},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34101349115371704},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.295249342918396},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29264843463897705}],"concepts":[{"id":"https://openalex.org/C156273044","wikidata":"https://www.wikidata.org/wiki/Q4913766","display_name":"Bin","level":2,"score":0.7409208416938782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6518049836158752},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6257190704345703},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.613909900188446},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5028302073478699},{"id":"https://openalex.org/C143392562","wikidata":"https://www.wikidata.org/wiki/Q449111","display_name":"Subdivision","level":2,"score":0.49390655755996704},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.47352027893066406},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.44399121403694153},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.44376638531684875},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.43137529492378235},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4250544309616089},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34101349115371704},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.295249342918396},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29264843463897705},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","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/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2022.3222457","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2022.3222457","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G2131151903","display_name":null,"funder_award_id":"42192580","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4308293926","display_name":null,"funder_award_id":"42192583","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5149724285","display_name":null,"funder_award_id":"2021CFA088","funder_id":"https://openalex.org/F4320322186","funder_display_name":"Natural Science Foundation of Hubei Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2088127691","https://openalex.org/W2771852828","https://openalex.org/W2787931417","https://openalex.org/W2790713095","https://openalex.org/W2891437844","https://openalex.org/W2913897408","https://openalex.org/W2963488291","https://openalex.org/W2963587345","https://openalex.org/W2969111887","https://openalex.org/W2975918238","https://openalex.org/W2984507463","https://openalex.org/W3033987687","https://openalex.org/W3081162165","https://openalex.org/W3096609285","https://openalex.org/W3107364113","https://openalex.org/W3110797472","https://openalex.org/W3120644635","https://openalex.org/W3138516171","https://openalex.org/W3173727695","https://openalex.org/W4229364371","https://openalex.org/W4245685703","https://openalex.org/W4297791811","https://openalex.org/W6693585675","https://openalex.org/W6748486149","https://openalex.org/W6778485988"],"related_works":["https://openalex.org/W2107701374","https://openalex.org/W2384806462","https://openalex.org/W4389950792","https://openalex.org/W2375549870","https://openalex.org/W2950072893","https://openalex.org/W4376632515","https://openalex.org/W1616588898","https://openalex.org/W2163269603","https://openalex.org/W4205312897","https://openalex.org/W4249504934"],"abstract_inverted_index":{"Height":[0],"estimation":[1,46,86],"from":[2],"a":[3,19,32,48,76,89,111,125,140,150],"single":[4,112],"remote":[5],"sensing":[6],"image":[7,132,157],"has":[8],"great":[9],"potential":[10],"in":[11,173],"generating":[12],"digital":[13],"surface":[14,22],"models":[15],"(DSM)":[16],"efficiently":[17],"for":[18,62,129,154],"quick":[20],"earth":[21],"reconstruction.":[23],"Recently,":[24],"convolutional":[25],"neural":[26],"networks":[27],"(CNN)":[28],"have":[29],"emerged":[30],"as":[31,47,88,139],"powerful":[33],"method":[34,191],"to":[35,52,65,71,92,110,115,123,171],"deal":[36],"with":[37,75,144],"this":[38,80],"ill-posed":[39],"problem.":[40,142],"Most":[41],"existing":[42],"methods":[43],"formulate":[44],"height":[45,85,103,165],"regression":[49],"problem":[50],"due":[51],"the":[53,63,67,72,84,94,100,116,136,145,159,164,174,177,189,193],"continuity":[54],"of":[55,176],"object":[56,68],"height.":[57],"However,":[58],"it":[59],"is":[60,168],"difficult":[61],"model":[64,95,160],"regress":[66],"heights":[69],"exactly":[70],"ground-truth":[73,102],"values":[74],"wide":[77],"range.":[78],"In":[79,119,180],"letter,":[81],"we":[82,98,121,183],"reformulate":[83],"task":[87,91],"classification":[90],"improve":[93],"performance.":[96],"Specifically,":[97],"discretize":[99],"continuous":[101],"into":[104],"bins":[105],"and":[106,185,199],"assign":[107],"each":[108,130,155],"pixel":[109],"label":[113],"according":[114],"bin":[117,127,137,147,152],"subdivision.":[118],"addition,":[120],"propose":[122],"generate":[124],"unique":[126],"subdivision":[128,148,153],"input":[131,156,178],"adaptively":[133,161],"by":[134],"viewing":[135],"generation":[138],"set-to-set":[141],"Compared":[143],"fixed":[146],"method,":[149],"specific":[151],"makes":[158],"focus":[162],"on":[163,196],"range":[166],"that":[167,188],"more":[169],"probable":[170],"occur":[172],"scene":[175],"image.":[179],"our":[181],"experiments,":[182],"qualitatively":[184],"quantitatively":[186],"demonstrate":[187],"proposed":[190],"outperforms":[192],"state-of-the-art":[194],"approaches":[195],"both":[197],"Vaihingen":[198],"Potsdam":[200],"datasets.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
