{"id":"https://openalex.org/W4402891714","doi":"https://doi.org/10.1109/tip.2024.3465034","title":"SRNSD: Structure-Regularized Night-Time Self-Supervised Monocular Depth Estimation for Outdoor Scenes","display_name":"SRNSD: Structure-Regularized Night-Time Self-Supervised Monocular Depth Estimation for Outdoor Scenes","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4402891714","doi":"https://doi.org/10.1109/tip.2024.3465034","pmid":"https://pubmed.ncbi.nlm.nih.gov/39325596"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2024.3465034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2024.3465034","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/A5091558139","display_name":"Runmin Cong","orcid":"https://orcid.org/0000-0003-0972-4008"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]},{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runmin Cong","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China","Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]},{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072254497","display_name":"Chunlei Wu","orcid":"https://orcid.org/0000-0002-0944-2564"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunlei Wu","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030165903","display_name":"Xibin Song","orcid":"https://orcid.org/0000-0001-7019-6238"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xibin Song","raw_affiliation_strings":["XR Vision Labs, Tencent, Shanghai, China","XR Vision Labs, Tencent, China"],"raw_orcid":"https://orcid.org/0000-0001-7019-6238","affiliations":[{"raw_affiliation_string":"XR Vision Labs, Tencent, Shanghai, China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"XR Vision Labs, Tencent, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100756634","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0002-4960-3190"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-4960-3190","affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008386708","display_name":"Sam Kwong","orcid":"https://orcid.org/0000-0001-7484-7261"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Sam Kwong","raw_affiliation_strings":["School of Data Science, Lingnan University, Hong Kong, SAR, China","Department of Computer Science, City University of Hong Kong, Hong Kong, SAR, China"],"raw_orcid":"https://orcid.org/0000-0001-7484-7261","affiliations":[{"raw_affiliation_string":"School of Data Science, Lingnan University, Hong Kong, SAR, China","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong, SAR, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101819061","display_name":"Hongdong Li","orcid":"https://orcid.org/0000-0003-4125-1554"},"institutions":[{"id":"https://openalex.org/I118347636","display_name":"Australian National University","ror":"https://ror.org/019wvm592","country_code":"AU","type":"education","lineage":["https://openalex.org/I118347636"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hongdong Li","raw_affiliation_strings":["College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia","College of Engineering and Computer Science, Australian National University, Australia"],"raw_orcid":"https://orcid.org/0000-0003-4125-1554","affiliations":[{"raw_affiliation_string":"College of Engineering and Computer Science, The Australian National University, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I118347636"]},{"raw_affiliation_string":"College of Engineering and Computer Science, Australian National University, Australia","institution_ids":["https://openalex.org/I118347636"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063587709","display_name":"Pan Ji","orcid":"https://orcid.org/0000-0001-6213-554X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pan Ji","raw_affiliation_strings":["XR Vision Labs, Tencent, Shanghai, China","XR Vision Labs, Tencent, China"],"raw_orcid":"https://orcid.org/0000-0001-6213-554X","affiliations":[{"raw_affiliation_string":"XR Vision Labs, Tencent, Shanghai, China","institution_ids":["https://openalex.org/I2250653659"]},{"raw_affiliation_string":"XR Vision Labs, Tencent, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6131,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.68136247,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"33","issue":null,"first_page":"5538","last_page":"5550"},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9966999888420105,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.993399977684021,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7230077981948853},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7017244100570679},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.617973804473877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.591519296169281},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3326374292373657}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7230077981948853},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7017244100570679},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.617973804473877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.591519296169281},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3326374292373657}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2024.3465034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2024.3465034","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:39325596","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39325596","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:openresearch-repository.anu.edu.au:1885/733750834","is_oa":false,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=85205421782&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S4306402539","display_name":"ANU Open Research (Australian National University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I118347636","host_organization_name":"Australian National University","host_organization_lineage":["https://openalex.org/I118347636"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"Journal article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1914386590","display_name":null,"funder_award_id":"62471278","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5593383844","display_name":null,"funder_award_id":"61991411","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/F4320336656","display_name":"Thousand Young Talents Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1677409904","https://openalex.org/W1731081199","https://openalex.org/W1905829557","https://openalex.org/W1915250530","https://openalex.org/W1942767339","https://openalex.org/W2028936041","https://openalex.org/W2099940712","https://openalex.org/W2108134361","https://openalex.org/W2115448105","https://openalex.org/W2122122381","https://openalex.org/W2124386111","https://openalex.org/W2124907686","https://openalex.org/W2148596671","https://openalex.org/W2520707372","https://openalex.org/W2535547924","https://openalex.org/W2558027072","https://openalex.org/W2609883120","https://openalex.org/W2798405286","https://openalex.org/W2895401575","https://openalex.org/W2948647700","https://openalex.org/W2962793481","https://openalex.org/W2962804601","https://openalex.org/W2963073614","https://openalex.org/W2963107255","https://openalex.org/W2963120918","https://openalex.org/W2963488291","https://openalex.org/W2964912923","https://openalex.org/W2981353488","https://openalex.org/W2981518351","https://openalex.org/W2985775862","https://openalex.org/W2988910664","https://openalex.org/W2995687155","https://openalex.org/W3003669105","https://openalex.org/W3014318259","https://openalex.org/W3033327942","https://openalex.org/W3034428934","https://openalex.org/W3034604951","https://openalex.org/W3035434014","https://openalex.org/W3035574168","https://openalex.org/W3035679448","https://openalex.org/W3043646556","https://openalex.org/W3082498369","https://openalex.org/W3089720635","https://openalex.org/W3126423155","https://openalex.org/W3152863269","https://openalex.org/W3157340408","https://openalex.org/W3167090845","https://openalex.org/W3174397558","https://openalex.org/W3175561084","https://openalex.org/W3177732058","https://openalex.org/W3194822352","https://openalex.org/W3202602509","https://openalex.org/W3206647015","https://openalex.org/W3211022685","https://openalex.org/W4249722514","https://openalex.org/W4383109207","https://openalex.org/W4390204136","https://openalex.org/W4390873354","https://openalex.org/W4392693764","https://openalex.org/W4402727359","https://openalex.org/W6631190155","https://openalex.org/W6685261749","https://openalex.org/W6725448924","https://openalex.org/W6730623217","https://openalex.org/W6733367512","https://openalex.org/W6858967322"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Deep":[0],"CNNs":[1],"have":[2],"achieved":[3],"impressive":[4],"improvements":[5],"for":[6,65,93,109,159],"night-time":[7,48,95,200],"self-supervised":[8,49,201],"depth":[9,23,51,71,90,99,111,130,157,177,202],"estimation":[10,24,52,203],"form":[11],"a":[12,46,142],"monocular":[13,50],"image.":[14],"However,":[15],"the":[16,125,135,163,193],"performance":[17],"degrades":[18],"considerably":[19],"compared":[20],"to":[21,26,123],"day-time":[22],"due":[25],"significant":[27],"domain":[28,72],"gaps,":[29],"low":[30],"visibility,":[31],"and":[32,37,70,77,89,98,105,113,127,166,181,189],"varying":[33],"illuminations":[34],"between":[35],"day":[36],"night":[38],"images.":[39],"To":[40],"address":[41],"these":[42],"challenges,":[43],"we":[44,83,117,140],"propose":[45],"novel":[47],"framework":[53],"with":[54,103,176],"structure":[55,112],"regularization,":[56],"i.e.,":[57],"SRNSD,":[58],"which":[59],"incorporates":[60],"three":[61],"aspects":[62],"of":[63,86,156,168,179,195],"constraints":[64],"better":[66,94,110,129],"performance,":[67],"including":[68,183],"feature":[69,88,96],"adaptation,":[73],"image":[74,120],"perspective":[75,121],"constraint,":[76],"cropped":[78,146],"multi-scale":[79,147],"consistency":[80,148,152],"loss.":[81],"Specifically,":[82],"utilize":[84],"adaptations":[85],"both":[87],"output":[91],"spaces":[92],"extraction":[97],"map":[100],"prediction,":[101],"along":[102],"high-":[104],"low-frequency":[106],"decoupling":[107],"operations":[108],"texture":[114],"recovery.":[115],"Meanwhile,":[116],"employ":[118],"an":[119],"constraint":[122],"enhance":[124],"smoothness":[126],"obtain":[128],"maps":[131],"in":[132],"areas":[133],"where":[134],"luminosity":[136],"jumps":[137],"change.":[138],"Furthermore,":[139],"introduce":[141],"simple":[143],"yet":[144],"effective":[145],"loss":[149],"that":[150],"utilizes":[151],"among":[153],"different":[154,174],"scales":[155],"outputs":[158],"further":[160],"optimization,":[161],"refining":[162],"detailed":[164],"textures":[165],"structures":[167],"predicted":[169],"depth.":[170],"Experimental":[171],"results":[172],"on":[173],"benchmarks":[175],"ranges":[178],"40m":[180],"60m,":[182],"Oxford":[184],"RobotCar":[185],"dataset,":[186,191],"nuScenes":[187],"dataset":[188],"CARLA-EPE":[190],"demonstrate":[192],"superiority":[194],"our":[196,209],"approach":[197],"over":[198],"state-of-the-art":[199],"approaches":[204],"across":[205],"multiple":[206],"metrics,":[207],"proving":[208],"effectiveness.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
