{"id":"https://openalex.org/W3192404838","doi":"https://doi.org/10.1109/iccv48922.2021.01000","title":"Self-Supervised Visual Representations Learning by Contrastive Mask Prediction","display_name":"Self-Supervised Visual Representations Learning by Contrastive Mask Prediction","publication_year":2021,"publication_date":"2021-10-01","ids":{"openalex":"https://openalex.org/W3192404838","doi":"https://doi.org/10.1109/iccv48922.2021.01000","mag":"3192404838"},"language":"en","primary_location":{"id":"doi:10.1109/iccv48922.2021.01000","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv48922.2021.01000","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101632793","display_name":"Yucheng Zhao","orcid":"https://orcid.org/0000-0002-9610-3025"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yucheng Zhao","raw_affiliation_strings":["University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060336107","display_name":"Guangting Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangting Wang","raw_affiliation_strings":["University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005976848","display_name":"Chong Luo","orcid":"https://orcid.org/0000-0003-4654-5682"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chong Luo","raw_affiliation_strings":["Microsoft Research Asia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049963367","display_name":"Wenjun Zeng","orcid":"https://orcid.org/0000-0003-2531-3137"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjun Zeng","raw_affiliation_strings":["Microsoft Research Asia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003217535","display_name":"Zheng-Jun Zha","orcid":"https://orcid.org/0000-0003-2510-8993"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng-Jun Zha","raw_affiliation_strings":["University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.6632,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.94591949,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"10140","last_page":"10149"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9991999864578247,"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":0.8167316317558289},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6908084154129028},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6069415211677551},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5505837798118591},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5230292081832886},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.41610392928123474},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.41547614336013794},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39611151814460754},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3266908526420593}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8167316317558289},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6908084154129028},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6069415211677551},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5505837798118591},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5230292081832886},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.41610392928123474},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.41547614336013794},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39611151814460754},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3266908526420593},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccv48922.2021.01000","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv48922.2021.01000","pdf_url":null,"source":{"id":"https://openalex.org/S4363607764","display_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5400000214576721},{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2250384498","https://openalex.org/W2321533354","https://openalex.org/W2326925005","https://openalex.org/W2732026016","https://openalex.org/W2785325870","https://openalex.org/W2798991696","https://openalex.org/W2842511635","https://openalex.org/W2883725317","https://openalex.org/W2886641317","https://openalex.org/W2896457183","https://openalex.org/W2912152775","https://openalex.org/W2938603906","https://openalex.org/W2963150697","https://openalex.org/W2963420272","https://openalex.org/W2963703197","https://openalex.org/W2990873191","https://openalex.org/W2997351497","https://openalex.org/W3005680577","https://openalex.org/W3009561768","https://openalex.org/W3034781633","https://openalex.org/W3035060554","https://openalex.org/W3035365026","https://openalex.org/W3035524453","https://openalex.org/W3036224891","https://openalex.org/W3046208551","https://openalex.org/W3110674625","https://openalex.org/W3168822201","https://openalex.org/W3172615411","https://openalex.org/W4287600707","https://openalex.org/W4297808394","https://openalex.org/W6639102338","https://openalex.org/W6676297131","https://openalex.org/W6700872662","https://openalex.org/W6701655646","https://openalex.org/W6747899497","https://openalex.org/W6755207826","https://openalex.org/W6761185680","https://openalex.org/W6774314701","https://openalex.org/W6774670964","https://openalex.org/W6779326418","https://openalex.org/W6779997284","https://openalex.org/W6781732661","https://openalex.org/W6784905488","https://openalex.org/W6785680793","https://openalex.org/W6786093290","https://openalex.org/W6786187962"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W4285260836","https://openalex.org/W3046775127","https://openalex.org/W2353865532","https://openalex.org/W2081647779","https://openalex.org/W3170094116"],"abstract_inverted_index":{"Advanced":[0],"self-supervised":[1,175],"visual":[2,48],"representation":[3,49],"learning":[4,50,176],"methods":[5,173],"rely":[6],"on":[7,118],"the":[8,18,60,76,84,107,110,113,171,178],"instance":[9],"discrimination":[10],"(ID)":[11],"pretext":[12],"task.":[13],"We":[14,115],"point":[15],"out":[16],"that":[17,133],"ID":[19],"task":[20,46],"has":[21],"an":[22],"implicit":[23],"semantic":[24],"consistency":[25],"(SC)":[26],"assumption,":[27],"which":[28,70],"may":[29],"not":[30],"hold":[31],"in":[32,99,177],"unconstrained":[33],"datasets.":[34],"In":[35],"this":[36],"paper,":[37],"we":[38,92],"propose":[39],"a":[40,53,94,147,151,167],"novel":[41],"contrastive":[42],"mask":[43,54,96],"prediction":[44,97],"(CMP)":[45],"for":[47,163,174],"and":[51,89,123],"design":[52,93],"contrast":[55],"(MaskCo)":[56],"framework":[57],"to":[58,74,105,109,170],"implement":[59],"idea.":[61],"MaskCo":[62,117,134,165],"contrasts":[63],"region-level":[64],"features":[65],"instead":[66],"of":[67,112,153],"view-level":[68],"features,":[69,91],"makes":[71],"it":[72],"possible":[73],"identify":[75],"positive":[77],"sample":[78],"without":[79],"any":[80],"assumptions.":[81],"To":[82],"solve":[83],"domain":[85],"gap":[86],"between":[87],"masked":[88],"unmasked":[90],"dedicated":[95],"head":[98],"MaskCo.":[100],"This":[101],"module":[102],"is":[103],"shown":[104],"be":[106],"key":[108],"success":[111],"CMP.":[114],"evaluated":[116],"training":[119,143],"datasets":[120],"beyond":[121],"ImageNet":[122,142],"compare":[124],"its":[125],"performance":[126,137,149],"with":[127,138],"MoCo":[128,139],"V2":[129,140],"[4].":[130],"Results":[131],"show":[132],"achieves":[135],"comparable":[136],"using":[141],"dataset,":[144],"but":[145],"demonstrates":[146],"stronger":[148],"across":[150],"range":[152],"downstream":[154],"tasks":[155],"when":[156],"COCO":[157],"or":[158],"Conceptual":[159],"Captions":[160],"are":[161],"used":[162],"training.":[164],"provides":[166],"promising":[168],"alternative":[169],"ID-based":[172],"wild.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
