{"id":"https://openalex.org/W4408017339","doi":"https://doi.org/10.1109/tci.2025.3545358","title":"NLCMR: Indoor Depth Recovery Model With Non-Local Cross-Modality Prior","display_name":"NLCMR: Indoor Depth Recovery Model With Non-Local Cross-Modality Prior","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408017339","doi":"https://doi.org/10.1109/tci.2025.3545358"},"language":"en","primary_location":{"id":"doi:10.1109/tci.2025.3545358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2025.3545358","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2334-0118","2573-0436"],"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 Computational Imaging","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/A5102973712","display_name":"Junkang Zhang","orcid":"https://orcid.org/0000-0002-1243-9139"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junkang Zhang","raw_affiliation_strings":["School of Computer Science and Technology, East China Norm University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-1243-9139","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Norm University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111141585","display_name":"Zhengkai Qi","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengkai Qi","raw_affiliation_strings":["School of Computer Science and Technology, East China Norm University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Norm University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044588347","display_name":"Faming Fang","orcid":"https://orcid.org/0000-0003-4511-4813"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Faming Fang","raw_affiliation_strings":["School of Computer Science and Technology, East China Norm University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4511-4813","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Norm University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447771","display_name":"Tingting Wang","orcid":"https://orcid.org/0009-0008-8433-8063"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingting Wang","raw_affiliation_strings":["School of Computer Science and Technology, East China Norm University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0008-8433-8063","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Norm University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060120202","display_name":"Guixu Zhang","orcid":"https://orcid.org/0000-0003-4720-6607"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guixu Zhang","raw_affiliation_strings":["School of Computer Science and Technology, East China Norm University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4720-6607","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Norm University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03431125,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"265","last_page":"276"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.995199978351593,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5326406955718994},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5120545029640198},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4871978163719177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38632792234420776},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.33826178312301636},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21137675642967224}],"concepts":[{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5326406955718994},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5120545029640198},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4871978163719177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38632792234420776},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.33826178312301636},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21137675642967224}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tci.2025.3545358","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2025.3545358","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2334-0118","2573-0436"],"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 Computational Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G7437995936","display_name":null,"funder_award_id":"62202173","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8541016986","display_name":null,"funder_award_id":"62271203","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":60,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1913661415","https://openalex.org/W1923184257","https://openalex.org/W1973059396","https://openalex.org/W1987648924","https://openalex.org/W2026203852","https://openalex.org/W2050849575","https://openalex.org/W2100556411","https://openalex.org/W2111650091","https://openalex.org/W2143291846","https://openalex.org/W2153388956","https://openalex.org/W2160547390","https://openalex.org/W2339170012","https://openalex.org/W2500602996","https://openalex.org/W2524856263","https://openalex.org/W2557465155","https://openalex.org/W2784344583","https://openalex.org/W2790567986","https://openalex.org/W2807828983","https://openalex.org/W2879448883","https://openalex.org/W2885093229","https://openalex.org/W2886851716","https://openalex.org/W2902486335","https://openalex.org/W2905472194","https://openalex.org/W2907260333","https://openalex.org/W2963045776","https://openalex.org/W2963867516","https://openalex.org/W2969202876","https://openalex.org/W2971303456","https://openalex.org/W2997891449","https://openalex.org/W2998031326","https://openalex.org/W3008618604","https://openalex.org/W3035302306","https://openalex.org/W3080631149","https://openalex.org/W3109128945","https://openalex.org/W3110653837","https://openalex.org/W3175561084","https://openalex.org/W3175720495","https://openalex.org/W3189360099","https://openalex.org/W3204305289","https://openalex.org/W3206335707","https://openalex.org/W4205516779","https://openalex.org/W4221146773","https://openalex.org/W4225592318","https://openalex.org/W4225987522","https://openalex.org/W4285153882","https://openalex.org/W4312725970","https://openalex.org/W4312734934","https://openalex.org/W4312901872","https://openalex.org/W4322765508","https://openalex.org/W4383200222","https://openalex.org/W4386075800","https://openalex.org/W4386524555","https://openalex.org/W4387623932","https://openalex.org/W4390872493","https://openalex.org/W4390873254","https://openalex.org/W4390873505","https://openalex.org/W4402779632","https://openalex.org/W4403944333","https://openalex.org/W6631190155"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","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":{"Recovering":[0],"a":[1,16,57,68,70,81,86,152],"dense":[2],"depth":[3,12,21,29,50,60,99,119],"image":[4,88,112],"from":[5],"sparse":[6,20],"inputs":[7],"is":[8,65,148],"inherently":[9],"challenging.":[10],"Image-guided":[11],"completion":[13],"has":[14],"become":[15],"prevalent":[17],"technique,":[18],"leveraging":[19],"data":[22,140],"alongside":[23],"RGB":[24,101,121],"images":[25],"to":[26,132],"produce":[27],"detailed":[28],"maps.":[30],"Although":[31],"deep":[32,87,111,177],"learning-based":[33],"methods":[34],"have":[35,136],"achieved":[36],"notable":[37],"success,":[38],"many":[39],"state-of-the-art":[40],"networks":[41],"operate":[42],"as":[43,151],"black":[44],"boxes,":[45],"lacking":[46],"transparent":[47],"mechanisms":[48],"for":[49],"recovery.":[51],"To":[52,124],"address":[53],"this,":[54],"we":[55,135],"introduce":[56],"novel":[58],"model-guided":[59],"recovery":[61],"method.":[62],"Our":[63,146],"approach":[64],"built":[66],"on":[67,94,161],"maximum":[69],"posterior":[71],"(MAP)":[72],"framework":[73],"and":[74,85,100,120,165],"features":[75],"an":[76,138],"optimization":[77],"model":[78,147],"that":[79,170],"incorporates":[80],"non-local":[82],"cross-modality":[83,91],"regularizer":[84,92],"prior.":[89],"The":[90],"capitalizes":[93],"the":[95,104,110,118,126,155,162],"inherent":[96],"correlations":[97],"between":[98,117],"images,":[102],"enhancing":[103],"extraction":[105],"of":[106,128],"shared":[107],"information.":[108],"Additionally,":[109],"prior":[113],"captures":[114],"local":[115],"characteristics":[116],"domains":[122],"effectively.":[123],"counter":[125],"challenge":[127],"high":[129],"heterogeneity":[130],"leading":[131],"degenerate":[133],"operators,":[134],"integrated":[137],"implicit":[139],"consistency":[141],"term":[142],"into":[143],"our":[144,171],"model.":[145],"then":[149],"realized":[150],"network":[153],"using":[154],"half-quadratic":[156],"splitting":[157],"algorithm.":[158],"Extensive":[159],"evaluations":[160],"NYU-Depth":[163],"V2":[164],"SUN":[166],"RGB-D":[167],"datasets":[168],"demonstrate":[169],"method":[172],"performs":[173],"competitively":[174],"with":[175],"current":[176],"learning":[178],"techniques.":[179]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
