{"id":"https://openalex.org/W7106274031","doi":"https://doi.org/10.1109/lra.2025.3635451","title":"Scale-Invariant and View-Relational Representation Learning for Full Surround Monocular Depth","display_name":"Scale-Invariant and View-Relational Representation Learning for Full Surround Monocular Depth","publication_year":2025,"publication_date":"2025-11-21","ids":{"openalex":"https://openalex.org/W7106274031","doi":"https://doi.org/10.1109/lra.2025.3635451"},"language":null,"primary_location":{"id":"doi:10.1109/lra.2025.3635451","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2025.3635451","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation 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":null,"display_name":"Kyumin Hwang","orcid":"https://orcid.org/0009-0000-7878-697X"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyumin Hwang","raw_affiliation_strings":["Department of Electrical Engineering &amp; Computer Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea"],"raw_orcid":"https://orcid.org/0009-0000-7878-697X","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering &amp; Computer Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wonhyeok Choi","orcid":"https://orcid.org/0009-0005-3270-8083"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wonhyeok Choi","raw_affiliation_strings":["Department of Artificial Intelligence, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea","Department of Electrical Engineering &amp; Computer Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea"],"raw_orcid":"https://orcid.org/0009-0005-3270-8083","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"Department of Electrical Engineering &amp; Computer Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kiljoon Han","orcid":"https://orcid.org/0009-0001-7276-8858"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kiljoon Han","raw_affiliation_strings":["Department of Artificial Intelligence, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea"],"raw_orcid":"https://orcid.org/0009-0001-7276-8858","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wonjoon Choi","orcid":"https://orcid.org/0009-0006-8271-2088"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wonjoon Choi","raw_affiliation_strings":["Department of Artificial Intelligence, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea","Department of Electrical Engineering &amp; Computer Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea"],"raw_orcid":"https://orcid.org/0009-0006-8271-2088","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"Department of Electrical Engineering &amp; Computer Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Minwoo Choi","orcid":"https://orcid.org/0009-0002-4379-1722"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minwoo Choi","raw_affiliation_strings":["Department of Electrical Engineering &amp; Computer Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea"],"raw_orcid":"https://orcid.org/0009-0002-4379-1722","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering &amp; Computer Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yongcheon Na","orcid":"https://orcid.org/0009-0001-2353-7762"},"institutions":[{"id":"https://openalex.org/I49946491","display_name":"Hyundai Motors (South Korea)","ror":"https://ror.org/016kvft77","country_code":"KR","type":"company","lineage":["https://openalex.org/I197312522","https://openalex.org/I49946491"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yongcheon Na","raw_affiliation_strings":["Department of Autonomous Driving Perception Technology Vanguard Team, Hyundai Motor Company, Gyeonggi, South Korea"],"raw_orcid":"https://orcid.org/0009-0001-2353-7762","affiliations":[{"raw_affiliation_string":"Department of Autonomous Driving Perception Technology Vanguard Team, Hyundai Motor Company, Gyeonggi, South Korea","institution_ids":["https://openalex.org/I49946491"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Minwoo Park","orcid":"https://orcid.org/0009-0004-7390-3013"},"institutions":[{"id":"https://openalex.org/I49946491","display_name":"Hyundai Motors (South Korea)","ror":"https://ror.org/016kvft77","country_code":"KR","type":"company","lineage":["https://openalex.org/I197312522","https://openalex.org/I49946491"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minwoo Park","raw_affiliation_strings":["Department of Autonomous Driving Perception Technology Vanguard Team, Hyundai Motor Company, Gyeonggi, South Korea"],"raw_orcid":"https://orcid.org/0009-0004-7390-3013","affiliations":[{"raw_affiliation_string":"Department of Autonomous Driving Perception Technology Vanguard Team, Hyundai Motor Company, Gyeonggi, South Korea","institution_ids":["https://openalex.org/I49946491"]}]},{"author_position":"last","author":{"id":null,"display_name":"Sunghoon Im","orcid":"https://orcid.org/0000-0001-9776-8101"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sunghoon Im","raw_affiliation_strings":["Department of Electrical Engineering &amp; Computer Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-9776-8101","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering &amp; Computer Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.48820679,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":"1","first_page":"1002","last_page":"1009"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9571999907493591,"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":0.9571999907493591,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.005100000184029341,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.0038999998942017555,"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/monocular","display_name":"Monocular","score":0.7142999768257141},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.7116000056266785},{"id":"https://openalex.org/keywords/bin","display_name":"Bin","score":0.5303999781608582},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.49939998984336853},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4731999933719635},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4641999900341034},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36079999804496765},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.3549000024795532}],"concepts":[{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.7142999768257141},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7125999927520752},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7116000056266785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6743000149726868},{"id":"https://openalex.org/C156273044","wikidata":"https://www.wikidata.org/wiki/Q4913766","display_name":"Bin","level":2,"score":0.5303999781608582},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5202000141143799},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.49939998984336853},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4731999933719635},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4641999900341034},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3671000003814697},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36079999804496765},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3375999927520752},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2815000116825104},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.2590999901294708},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2025.3635451","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2025.3635451","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"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 Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2115579991","https://openalex.org/W2473930607","https://openalex.org/W2963140444","https://openalex.org/W2963488291","https://openalex.org/W2964014680","https://openalex.org/W2968529893","https://openalex.org/W2982242214","https://openalex.org/W2982247743","https://openalex.org/W2985775862","https://openalex.org/W3034604951","https://openalex.org/W3035574168","https://openalex.org/W3141975725","https://openalex.org/W3173274332","https://openalex.org/W3173727695","https://openalex.org/W3176193798","https://openalex.org/W3177390622","https://openalex.org/W4214520160","https://openalex.org/W4249736682","https://openalex.org/W4312904920","https://openalex.org/W4312929415","https://openalex.org/W4312933868","https://openalex.org/W4321512633","https://openalex.org/W4385800744","https://openalex.org/W4388624330","https://openalex.org/W4390871795","https://openalex.org/W4390872043","https://openalex.org/W4390874575","https://openalex.org/W4391926995","https://openalex.org/W4399938885","https://openalex.org/W4402727359","https://openalex.org/W4405786589","https://openalex.org/W4415798746"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"foundation":[1,71,118],"models":[2,15,44],"demonstrate":[3,163],"strong":[4],"generalization":[5],"capabilities":[6],"in":[7,38,91],"monocular":[8],"depth":[9,67,94,113,130,156],"estimation.":[10],"However,":[11],"directly":[12],"applying":[13],"these":[14,43,55],"to":[16,48,73,97,127,153,170],"Full":[17],"Surround":[18],"Monocular":[19],"Depth":[20],"Estimation":[21],"(FSMDE)":[22],"presents":[23],"two":[24],"major":[25],"challenges:":[26],"(1)":[27],"high":[28],"computational":[29],"cost,":[30],"which":[31,142],"limits":[32],"real-time":[33,191],"performance,":[34],"and":[35,150,161,174,188],"(2)":[36],"difficulty":[37],"estimating":[39],"metric-scale":[40,129],"depth,":[41],"as":[42],"are":[45],"typically":[46],"trained":[47],"predict":[49],"only":[50],"relative":[51],"depth.":[52,135],"To":[53],"address":[54],"limitations,":[56],"we":[57,102,137],"propose":[58,138],"a":[59,70,74,81,93,104,117,183],"novel":[60],"knowledge":[61,68,87,106,140,176],"distillation":[62,88,107,177],"strategy":[63],"that":[64,109],"transfers":[65,151],"robust":[66],"from":[69,133],"model":[72,119],"lightweight":[75],"FSMDE":[76],"network.":[77],"Our":[78],"approach":[79],"leverages":[80],"hybrid":[82],"regression":[83],"framework":[84],"combining":[85],"the":[86,111,121,164],"scheme\u2013traditionally":[89],"used":[90],"classification\u2013with":[92],"binning":[95],"module":[96],"enhance":[98,154],"scale":[99],"consistency.":[100,157],"Specifically,":[101],"introduce":[103],"cross-interaction":[105],"scheme":[108],"distills":[110],"scale-invariant":[112],"bin":[114,131],"probabilities":[115],"of":[116,166],"into":[120],"student":[122],"network":[123],"while":[124],"guiding":[125],"it":[126],"infer":[128],"centers":[132],"ground-truth":[134],"Furthermore,":[136],"view-relational":[139],"distillation,":[141],"encodes":[143],"structural":[144],"relationships":[145],"among":[146],"adjacent":[147],"camera":[148],"views":[149],"them":[152],"cross-view":[155],"Experiments":[158],"on":[159],"DDAD":[160],"nuScenes":[162],"effectiveness":[165],"our":[167,180],"method":[168,181],"compared":[169],"conventional":[171],"supervised":[172],"methods":[173],"existing":[175],"approaches.":[178],"Moreover,":[179],"achieves":[182],"favorable":[184],"trade-off":[185],"between":[186],"performance":[187],"efficiency,":[189],"meeting":[190],"requirements.":[192]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-11-23T00:00:00"}
