{"id":"https://openalex.org/W3210474784","doi":"https://doi.org/10.1109/tpami.2021.3123843","title":"Unsupervised Domain Adaptation of Deep Networks for ToF Depth Refinement","display_name":"Unsupervised Domain Adaptation of Deep Networks for ToF Depth Refinement","publication_year":2021,"publication_date":"2021-10-29","ids":{"openalex":"https://openalex.org/W3210474784","doi":"https://doi.org/10.1109/tpami.2021.3123843","mag":"3210474784","pmid":"https://pubmed.ncbi.nlm.nih.gov/34714740"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2021.3123843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2021.3123843","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","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/A5010490677","display_name":"Gianluca Agresti","orcid":"https://orcid.org/0000-0001-7072-0079"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gianluca Agresti","raw_affiliation_strings":["Sony R&D Center Europe Stuttgart Laboratory 1, Stuttgart, Germany"],"raw_orcid":"https://orcid.org/0000-0001-7072-0079","affiliations":[{"raw_affiliation_string":"Sony R&D Center Europe Stuttgart Laboratory 1, Stuttgart, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111710732","display_name":"Henrik Sch\u00e4fer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Henrik Schafer","raw_affiliation_strings":["Sony R&D Center Europe Stuttgart Laboratory 1, Stuttgart, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sony R&D Center Europe Stuttgart Laboratory 1, Stuttgart, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033349094","display_name":"Piergiorgio Sartor","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Piergiorgio Sartor","raw_affiliation_strings":["Sony R&D Center Europe Stuttgart Laboratory 1, Stuttgart, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sony R&D Center Europe Stuttgart Laboratory 1, Stuttgart, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012511781","display_name":"Yalcin Incesu","orcid":"https://orcid.org/0000-0001-6480-3724"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yalcin Incesu","raw_affiliation_strings":["Sony R&D Center Europe Stuttgart Laboratory 1, Stuttgart, Germany"],"raw_orcid":"https://orcid.org/0000-0001-6480-3724","affiliations":[{"raw_affiliation_string":"Sony R&D Center Europe Stuttgart Laboratory 1, Stuttgart, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070777118","display_name":"Pietro Zanuttigh","orcid":"https://orcid.org/0000-0002-9502-2389"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Pietro Zanuttigh","raw_affiliation_strings":["University of Padova, Padova, Italy"],"raw_orcid":"https://orcid.org/0000-0002-9502-2389","affiliations":[{"raw_affiliation_string":"University of Padova, Padova, Italy","institution_ids":["https://openalex.org/I138689650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0364,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.79036677,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"44","issue":"12","first_page":"9195","last_page":"9208"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9977999925613403,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9977999925613403,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9976999759674072,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7947916984558105},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.7407289743423462},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6766059398651123},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6614514589309692},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5085827112197876},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.5001943111419678},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4436042010784149},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.08866295218467712}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7947916984558105},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.7407289743423462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6766059398651123},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6614514589309692},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5085827112197876},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.5001943111419678},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4436042010784149},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.08866295218467712},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tpami.2021.3123843","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2021.3123843","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:34714740","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34714740","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 pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:www.research.unipd.it:11577/3411063","is_oa":false,"landing_page_url":"https://hdl.handle.net/11577/3411063","pdf_url":null,"source":{"id":"https://openalex.org/S4377196283","display_name":"Research Padua  Archive (University of Padua)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W75517964","https://openalex.org/W134016981","https://openalex.org/W1522301498","https://openalex.org/W1527354995","https://openalex.org/W1826919311","https://openalex.org/W1882958252","https://openalex.org/W1983193557","https://openalex.org/W1984241286","https://openalex.org/W2016620160","https://openalex.org/W2023021573","https://openalex.org/W2040013021","https://openalex.org/W2042375436","https://openalex.org/W2131653896","https://openalex.org/W2159291411","https://openalex.org/W2168894291","https://openalex.org/W2177564859","https://openalex.org/W2235602151","https://openalex.org/W2314059154","https://openalex.org/W2318193839","https://openalex.org/W2486979733","https://openalex.org/W2584009249","https://openalex.org/W2593414223","https://openalex.org/W2595014588","https://openalex.org/W2607512710","https://openalex.org/W2738545246","https://openalex.org/W2768145272","https://openalex.org/W2768431869","https://openalex.org/W2768591600","https://openalex.org/W2787942540","https://openalex.org/W2792274244","https://openalex.org/W2799224898","https://openalex.org/W2884480653","https://openalex.org/W2912555761","https://openalex.org/W2913338262","https://openalex.org/W2914535147","https://openalex.org/W2948497665","https://openalex.org/W2954563178","https://openalex.org/W2962793481","https://openalex.org/W2962808524","https://openalex.org/W2962874294","https://openalex.org/W2963709863","https://openalex.org/W2963870446","https://openalex.org/W2964159141","https://openalex.org/W2964278684","https://openalex.org/W2964288524","https://openalex.org/W2965954137","https://openalex.org/W2972581288","https://openalex.org/W2980196494","https://openalex.org/W2989809735","https://openalex.org/W3010577160","https://openalex.org/W3023078916","https://openalex.org/W3026575546","https://openalex.org/W3102597069","https://openalex.org/W3106403396","https://openalex.org/W3131502115","https://openalex.org/W3135228757","https://openalex.org/W4320013936","https://openalex.org/W6631190155","https://openalex.org/W6639480849","https://openalex.org/W6660835008","https://openalex.org/W6683633756","https://openalex.org/W6689185339","https://openalex.org/W6690003421","https://openalex.org/W6713955831","https://openalex.org/W6720111944","https://openalex.org/W6731344955","https://openalex.org/W6736210646","https://openalex.org/W6746262046","https://openalex.org/W6746282794","https://openalex.org/W6758693029","https://openalex.org/W6758912383","https://openalex.org/W6910569109"],"related_works":["https://openalex.org/W4280544492","https://openalex.org/W4312963184","https://openalex.org/W4224936630","https://openalex.org/W4225274307","https://openalex.org/W2942006347","https://openalex.org/W2441762250","https://openalex.org/W2057836452","https://openalex.org/W2986766740","https://openalex.org/W2942881172","https://openalex.org/W3210474784"],"abstract_inverted_index":{"Depth":[0],"maps":[1],"acquired":[2],"with":[3,37,163],"ToF":[4,28,122],"cameras":[5],"have":[6],"a":[7,83,125,164],"limited":[8],"accuracy":[9],"due":[10],"to":[11,17,45,51,77,89,118,128,135,143,150,167,173,190],"the":[12,18,58,62,68,98,101,105,109,137,145,169,175,185],"high":[13],"noise":[14],"level":[15,107],"and":[16,43,64,103,152,195],"multi-path":[19],"interference.":[20],"Deep":[21],"networks":[22,53,117],"can":[23],"be":[24],"used":[25,134],"for":[26],"refining":[27],"depth,":[29],"but":[30,57],"their":[31],"training":[32],"requires":[33],"real":[34,63,90,129,153,179],"world":[35],"acquisitions":[36],"ground":[38,170],"truth,":[39],"which":[40],"is":[41,50,132],"complex":[42],"expensive":[44],"collect.":[46],"A":[47],"possible":[48],"workaround":[49],"train":[52,136,174],"on":[54,177],"synthetic":[55,65,88,121,151],"data,":[56,130],"domain":[59,80,115],"shift":[60],"between":[61],"data":[66,123],"reduces":[67],"performances.":[69,199],"In":[70],"this":[71],"paper,":[72],"we":[73],"propose":[74],"three":[75],"approaches":[76,93,187],"perform":[78],"unsupervised":[79],"adaptation":[81],"of":[82,108],"depth":[84],"denoising":[85,198],"network":[86,146],"from":[87],"data.":[91,154,180],"These":[92],"are":[94,188],"respectively":[95],"acting":[96],"at":[97,100,104],"input,":[99],"feature":[102],"output":[106],"network.":[110],"The":[111,139,155],"first":[112],"approach":[113,141,157],"uses":[114,158],"translation":[116],"transform":[119],"labeled":[120],"into":[124],"representation":[126],"closer":[127],"that":[131,184],"then":[133],"denoiser.":[138],"second":[140],"tries":[142],"align":[144],"internal":[147],"features":[148],"related":[149],"third":[156],"an":[159],"adversarial":[160],"loss,":[161],"implemented":[162],"discriminator":[165],"trained":[166],"recognize":[168],"truth":[171],"statistic,":[172],"denoiser":[176],"unlabeled":[178],"Experimental":[181],"results":[182],"show":[183],"considered":[186],"able":[189],"outperform":[191],"other":[192],"state-of-the-art":[193],"techniques":[194],"achieve":[196],"superior":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}