{"id":"https://openalex.org/W4367047204","doi":"https://doi.org/10.1145/3543507.3583445","title":"DANCE: Learning A Domain Adaptive Framework for Deep Hashing","display_name":"DANCE: Learning A Domain Adaptive Framework for Deep Hashing","publication_year":2023,"publication_date":"2023-04-26","ids":{"openalex":"https://openalex.org/W4367047204","doi":"https://doi.org/10.1145/3543507.3583445"},"language":"en","primary_location":{"id":"doi:10.1145/3543507.3583445","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583445","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583445","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583445","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100617262","display_name":"Haixin Wang","orcid":"https://orcid.org/0000-0002-5714-0149"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haixin Wang","raw_affiliation_strings":["Peking University, China"],"raw_orcid":"https://orcid.org/0000-0002-5714-0149","affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072710764","display_name":"Jinan Sun","orcid":"https://orcid.org/0000-0001-8138-9262"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinan Sun","raw_affiliation_strings":["Peking University, China"],"raw_orcid":"https://orcid.org/0000-0001-8138-9262","affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001181973","display_name":"Wei Xiang","orcid":"https://orcid.org/0000-0001-5267-3184"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiang Wei","raw_affiliation_strings":["BIGO Inc., Singapore"],"raw_orcid":"https://orcid.org/0000-0001-5267-3184","affiliations":[{"raw_affiliation_string":"BIGO Inc., Singapore","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101435571","display_name":"Shikun Zhang","orcid":"https://orcid.org/0000-0002-8576-2674"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shikun Zhang","raw_affiliation_strings":["Peking University, China"],"raw_orcid":"https://orcid.org/0000-0002-8576-2674","affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100348795","display_name":"Chong Chen","orcid":"https://orcid.org/0000-0003-0213-9957"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chong Chen","raw_affiliation_strings":["Peking University, China"],"raw_orcid":"https://orcid.org/0000-0003-0213-9957","affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024965898","display_name":"Xian\u2010Sheng Hua","orcid":"https://orcid.org/0000-0002-8232-5049"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xian-Sheng Hua","raw_affiliation_strings":["Zhejiang University, China"],"raw_orcid":"https://orcid.org/0000-0002-8232-5049","affiliations":[{"raw_affiliation_string":"Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100426938","display_name":"Xiao Luo","orcid":"https://orcid.org/0000-0002-7987-3714"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao Luo","raw_affiliation_strings":["Department of Computer Science, UCLA, USA"],"raw_orcid":"https://orcid.org/0000-0002-7987-3714","affiliations":[{"raw_affiliation_string":"Department of Computer Science, UCLA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4557,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.88184818,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3319","last_page":"3330"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9997000098228455,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9980000257492065,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9951000213623047,"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":0.7672780156135559},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.6732231378555298},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5774134397506714},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5688221454620361},{"id":"https://openalex.org/keywords/locality-sensitive-hashing","display_name":"Locality-sensitive hashing","score":0.5607861280441284},{"id":"https://openalex.org/keywords/feature-hashing","display_name":"Feature hashing","score":0.5328158736228943},{"id":"https://openalex.org/keywords/universal-hashing","display_name":"Universal hashing","score":0.510597288608551},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.4260501265525818},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36650827527046204},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35417085886001587},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32757335901260376},{"id":"https://openalex.org/keywords/hash-table","display_name":"Hash table","score":0.2396324872970581},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2175634205341339},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11923617124557495},{"id":"https://openalex.org/keywords/double-hashing","display_name":"Double hashing","score":0.08028817176818848}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7672780156135559},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.6732231378555298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5774134397506714},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5688221454620361},{"id":"https://openalex.org/C74270461","wikidata":"https://www.wikidata.org/wiki/Q1625299","display_name":"Locality-sensitive hashing","level":4,"score":0.5607861280441284},{"id":"https://openalex.org/C133667856","wikidata":"https://www.wikidata.org/wiki/Q5439682","display_name":"Feature hashing","level":5,"score":0.5328158736228943},{"id":"https://openalex.org/C116058348","wikidata":"https://www.wikidata.org/wiki/Q846912","display_name":"Universal hashing","level":5,"score":0.510597288608551},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.4260501265525818},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36650827527046204},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35417085886001587},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32757335901260376},{"id":"https://openalex.org/C67388219","wikidata":"https://www.wikidata.org/wiki/Q207440","display_name":"Hash table","level":3,"score":0.2396324872970581},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2175634205341339},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11923617124557495},{"id":"https://openalex.org/C138111711","wikidata":"https://www.wikidata.org/wiki/Q478351","display_name":"Double hashing","level":4,"score":0.08028817176818848},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3543507.3583445","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583445","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583445","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3543507.3583445","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3543507.3583445","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3543507.3583445","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4367047204.pdf","grobid_xml":"https://content.openalex.org/works/W4367047204.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W74601114","https://openalex.org/W1489843519","https://openalex.org/W1722318740","https://openalex.org/W1974647172","https://openalex.org/W2040918046","https://openalex.org/W2057266281","https://openalex.org/W2100659887","https://openalex.org/W2112796928","https://openalex.org/W2411707397","https://openalex.org/W2602753196","https://openalex.org/W2627183927","https://openalex.org/W2749777401","https://openalex.org/W2765440071","https://openalex.org/W2766724094","https://openalex.org/W2795832645","https://openalex.org/W2798702669","https://openalex.org/W2799787995","https://openalex.org/W2890032859","https://openalex.org/W2922521335","https://openalex.org/W2945806531","https://openalex.org/W2962687275","https://openalex.org/W2964158883","https://openalex.org/W2966088020","https://openalex.org/W2967957126","https://openalex.org/W2975761438","https://openalex.org/W2978274700","https://openalex.org/W2980096013","https://openalex.org/W2981496068","https://openalex.org/W3012642003","https://openalex.org/W3012833893","https://openalex.org/W3034239448","https://openalex.org/W3034315422","https://openalex.org/W3034971598","https://openalex.org/W3035524453","https://openalex.org/W3035732386","https://openalex.org/W3087124270","https://openalex.org/W3093265782","https://openalex.org/W3114063012","https://openalex.org/W3127270411","https://openalex.org/W3144310280","https://openalex.org/W3153783849","https://openalex.org/W3154134332","https://openalex.org/W3154887397","https://openalex.org/W3155638432","https://openalex.org/W3155787390","https://openalex.org/W3187985423","https://openalex.org/W3188087362","https://openalex.org/W3207182362","https://openalex.org/W4214697508","https://openalex.org/W4220690485","https://openalex.org/W4224241592","https://openalex.org/W4224324956","https://openalex.org/W4225580830","https://openalex.org/W4226333663","https://openalex.org/W4285604435","https://openalex.org/W4288101202","https://openalex.org/W4297969478","https://openalex.org/W4304092162","https://openalex.org/W4312416205","https://openalex.org/W4312496732","https://openalex.org/W4312601326","https://openalex.org/W4319878852"],"related_works":["https://openalex.org/W1998749283","https://openalex.org/W2088296667","https://openalex.org/W1554555624","https://openalex.org/W2100189723","https://openalex.org/W2767764284","https://openalex.org/W2171626009","https://openalex.org/W2035647105","https://openalex.org/W3192973254","https://openalex.org/W3158263601","https://openalex.org/W2584541861"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"unsupervised":[3],"domain":[4,18,35,54,84,185,203],"adaptive":[5,85,204],"hashing,":[6],"which":[7,183],"aims":[8],"to":[9,19,94,114,155,215],"transfer":[10],"a":[11,15,20,73,177,199,216],"hashing":[12,40,117],"model":[13,194],"from":[14,46,101],"label-rich":[16],"source":[17,122,169],"label-scarce":[21],"target":[22,135,171],"domain.":[23,123],"Current":[24],"state-of-the-art":[25],"approaches":[26],"generally":[27],"resolve":[28],"the":[29,58,61,121,134,146,157,163,188,193,208],"problem":[30],"by":[31,57],"integrating":[32],"pseudo-labeling":[33],"and":[34,52,105,127,170,173],"adaptation":[36],"techniques":[37],"into":[38,176],"deep":[39],"paradigms.":[41],"Nevertheless,":[42],"they":[43],"usually":[44],"suffer":[45],"serious":[47],"class":[48],"imbalance":[49],"in":[50,120,133,145,167,187,221],"pseudo-labels":[51,129],"suboptimal":[53],"alignment":[55,186],"caused":[56],"neglection":[59],"of":[60,64,90,201,210,218],"intrinsic":[62],"structures":[63],"two":[65],"domains.":[66],"To":[67,108,124],"address":[68],"this":[69],"issue,":[70],"we":[71,137,161],"propose":[72],"novel":[74],"method":[75],"named":[76],"unbiaseD":[77],"duAl":[78],"hashiNg":[79],"Contrastive":[80],"lEarning":[81],"(DANCE)":[82],"for":[83,130],"image":[86],"retrieval.":[87],"The":[88],"core":[89],"our":[91,211],"DANCE":[92,110,213],"is":[93,152],"perform":[95],"contrastive":[96,118,180],"learning":[97,119,132,181],"on":[98,198],"hash":[99],"codes":[100],"both":[102,168],"instance":[103],"level":[104],"prototype":[106,165],"level.":[107],"begin,":[109],"utilizes":[111],"label":[112,143],"information":[113],"guide":[115],"instance-level":[116],"generate":[125],"unbiased":[126],"reliable":[128],"semantic":[131,164],"domain,":[136],"uniformly":[138],"select":[139],"samples":[140],"around":[141],"each":[142],"embedding":[144],"Hamming":[147,189],"space.":[148],"A":[149],"momentum-update":[150],"scheme":[151],"also":[153],"utilized":[154],"smooth":[156],"optimization":[158],"process.":[159],"Additionally,":[160],"measure":[162],"representations":[166],"domains":[172],"incorporate":[174],"them":[175],"domain-aware":[178],"prototype-level":[179],"paradigm,":[182],"enhances":[184],"space":[190],"while":[191],"maximizing":[192],"capacity.":[195],"Experimental":[196],"results":[197],"number":[200],"well-known":[202],"retrieval":[205],"benchmarks":[206],"validate":[207],"effectiveness":[209],"proposed":[212],"compared":[214],"variety":[217],"competing":[219],"baselines":[220],"different":[222],"settings.":[223]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
