{"id":"https://openalex.org/W4385681423","doi":"https://doi.org/10.1145/3581783.3611808","title":"Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration Error","display_name":"Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration Error","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4385681423","doi":"https://doi.org/10.1145/3581783.3611808"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3611808","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2308.03003","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100727966","display_name":"Zixin Wang","orcid":"https://orcid.org/0000-0002-2180-7204"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Zixin Wang","raw_affiliation_strings":["The University of Queensland, Brisbane, QLD, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Queensland, Brisbane, QLD, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063603492","display_name":"Yadan Luo","orcid":"https://orcid.org/0000-0001-6272-2971"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yadan Luo","raw_affiliation_strings":["The University of Queensland, Brisbane, QLD, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Queensland, Brisbane, QLD, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100456835","display_name":"Zhi Chen","orcid":"https://orcid.org/0000-0002-9385-144X"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zhi Chen","raw_affiliation_strings":["The University of Queensland, Brisbane, QLD, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Queensland, Brisbane, QLD, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350745","display_name":"Sen Wang","orcid":"https://orcid.org/0000-0002-5414-8276"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sen Wang","raw_affiliation_strings":["The University of Queensland, Brisbane, QLD, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Queensland, Brisbane, QLD, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078170935","display_name":"Zi Huang","orcid":"https://orcid.org/0000-0002-9738-4949"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zi Huang","raw_affiliation_strings":["The University of Queensland, Brisbane, QLD, Australia"],"affiliations":[{"raw_affiliation_string":"The University of Queensland, Brisbane, QLD, Australia","institution_ids":["https://openalex.org/I165143802"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100727966"],"corresponding_institution_ids":["https://openalex.org/I165143802"],"apc_list":null,"apc_paid":null,"fwci":2.4355,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.91089321,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1167","last_page":"1178"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9843000173568726,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9563000202178955,"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/computer-science","display_name":"Computer science","score":0.7512561082839966},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6320852041244507},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5587208867073059},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.5102026462554932},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4880034029483795},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.453172504901886},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45288941264152527},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32361388206481934},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22343146800994873},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1373136043548584}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7512561082839966},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6320852041244507},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5587208867073059},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.5102026462554932},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4880034029483795},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.453172504901886},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45288941264152527},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32361388206481934},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22343146800994873},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1373136043548584},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3581783.3611808","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3611808","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2308.03003","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2308.03003","pdf_url":"https://arxiv.org/pdf/2308.03003","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2308.03003","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2308.03003","pdf_url":"https://arxiv.org/pdf/2308.03003","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.46000000834465027}],"awards":[{"id":"https://openalex.org/G3971245475","display_name":null,"funder_award_id":"DE200101610","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385681423.pdf"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W1582774210","https://openalex.org/W1598033630","https://openalex.org/W1599263113","https://openalex.org/W1618905105","https://openalex.org/W2194775991","https://openalex.org/W2254249950","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2431874326","https://openalex.org/W2487365028","https://openalex.org/W2548695521","https://openalex.org/W2560674852","https://openalex.org/W2626967530","https://openalex.org/W2747329762","https://openalex.org/W2786808285","https://openalex.org/W2884771968","https://openalex.org/W2895281799","https://openalex.org/W2963073217","https://openalex.org/W2963107255","https://openalex.org/W2971118045","https://openalex.org/W2974098375","https://openalex.org/W2979509742","https://openalex.org/W2981429991","https://openalex.org/W2981873476","https://openalex.org/W2981952612","https://openalex.org/W2985406498","https://openalex.org/W2986831462","https://openalex.org/W3007404550","https://openalex.org/W3034526587","https://openalex.org/W3034562924","https://openalex.org/W3035294798","https://openalex.org/W3092738584","https://openalex.org/W3102977943","https://openalex.org/W3118629228","https://openalex.org/W3134134173","https://openalex.org/W3169652053","https://openalex.org/W3173206925","https://openalex.org/W3175042385","https://openalex.org/W3177192381","https://openalex.org/W3179941346","https://openalex.org/W3185527523","https://openalex.org/W3199495496","https://openalex.org/W3201774370","https://openalex.org/W3203048322","https://openalex.org/W3205534937","https://openalex.org/W3205594649","https://openalex.org/W3206487064","https://openalex.org/W3211727381","https://openalex.org/W3213646008","https://openalex.org/W4226396592","https://openalex.org/W4229482837","https://openalex.org/W4283075205","https://openalex.org/W4287063406","https://openalex.org/W4287325357","https://openalex.org/W4287755125","https://openalex.org/W4287865413","https://openalex.org/W4293517992","https://openalex.org/W4293518937","https://openalex.org/W4300772090","https://openalex.org/W4322717464","https://openalex.org/W4366352743","https://openalex.org/W6600284113"],"related_works":["https://openalex.org/W4285277090","https://openalex.org/W4327738859","https://openalex.org/W2348722996","https://openalex.org/W2334570605","https://openalex.org/W3181683615","https://openalex.org/W4286826125","https://openalex.org/W1633485514","https://openalex.org/W1604739066","https://openalex.org/W2115878407","https://openalex.org/W1980454230"],"abstract_inverted_index":{"The":[0,100,130,212],"prevalence":[1],"of":[2,120,162,221,258],"domain":[3,12,21,38,94,190],"adaptive":[4,95],"semantic":[5,96],"segmentation":[6,97,113],"has":[7,40],"prompted":[8],"concerns":[9],"regarding":[10],"source":[11,20,35,145,156,179],"data":[13],"leakage,":[14],"where":[15],"private":[16],"information":[17],"from":[18,111],"the":[19,27,32,56,59,63,106,112,121,126,137,155,160,163,168,177,188,219,230,248],"could":[22],"inadvertently":[23],"be":[24],"exposed":[25],"in":[26,134,143,217],"target":[28,60,128,148,189],"domain.":[29,129],"To":[30,183],"circumvent":[31],"requirement":[33],"for":[34,181,199,210],"data,":[36],"source-free":[37,93],"adaptation":[39,149,231],"emerged":[41],"as":[42,116],"a":[43,90,117,196],"viable":[44],"solution":[45],"that":[46,247],"leverages":[47],"self-training":[48],"methods":[49],"to":[50,58,72,104,125,175,256],"pseudo-label":[51],"high-confidence":[52],"regions":[53],"and":[54,74,82,140,147,171,202,223,233],"adapt":[55],"model":[57,80,138,152,262],"data.":[61],"However,":[62],"confidence":[64],"scores":[65,174,215],"obtained":[66],"are":[67],"often":[68],"highly":[69],"biased":[70],"due":[71],"overconfidence":[73],"class-imbalance":[75],"issues,":[76],"which":[77],"render":[78],"both":[79,144],"selection":[81,142,263],"optimization":[83],"problematic.":[84],"In":[85],"this":[86],"paper,":[87],"we":[88,158,194],"propose":[89],"novel":[91],"calibration-guided":[92],"(Cal-SFDA)":[98],"framework.":[99],"core":[101],"idea":[102],"is":[103],"estimate":[105],"expected":[107],"calibration":[108],"error":[109,236],"(ECE)":[110],"predictions,":[114],"serving":[115],"strong":[118],"indicator":[119],"model's":[122],"generalization":[123],"capability":[124],"unlabeled":[127],"estimated":[131,213],"ECE":[132,164,173,185,200,214],"scores,":[133],"turn,":[135],"assist":[136,216],"training":[139,146],"fair":[141,261],"stages.":[150],"During":[151],"pre-training":[153],"on":[154,187,206,240],"domain,":[157],"ensure":[159],"differentiability":[161],"objective":[165],"by":[166,227,254],"leveraging":[167],"LogSumExp":[169],"trick":[170],"using":[172],"select":[176],"best":[178],"checkpoints":[180],"adaptation.":[182],"enable":[184,224],"estimation":[186,201],"without":[191],"requiring":[192],"labels,":[193],"train":[195],"value":[197],"net":[198],"apply":[203],"statistic":[204],"warm-up":[205],"its":[207],"BatchNorm":[208],"layers":[209],"stability.":[211],"determining":[218],"reliability":[220],"prediction":[222],"class-balanced":[225],"pseudo-labeling":[226],"positively":[228],"guiding":[229],"progress":[232],"inhibiting":[234],"potential":[235],"accumulation.":[237],"Extensive":[238],"experiments":[239],"two":[241],"widely-used":[242],"synthetic-to-real":[243],"transfer":[244],"tasks":[245],"show":[246],"proposed":[249],"approach":[250],"surpasses":[251],"previous":[252],"state-of-the-art":[253],"up":[255],"5.25%":[257],"mIoU":[259],"with":[260],"criteria.":[264]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
