{"id":"https://openalex.org/W2620982237","doi":"https://doi.org/10.24963/ijcai.2017/410","title":"Instance-Level Label Propagation with Multi-Instance Learning","display_name":"Instance-Level Label Propagation with Multi-Instance Learning","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2620982237","doi":"https://doi.org/10.24963/ijcai.2017/410","mag":"2620982237"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2017/410","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/410","pdf_url":"https://www.ijcai.org/proceedings/2017/0410.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2017/0410.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101774659","display_name":"Qifan Wang","orcid":"https://orcid.org/0000-0002-7570-5756"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qifan Wang","raw_affiliation_strings":["Google Research","Google Research Mountain View, CA 94043, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research Mountain View, CA 94043, US","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045719865","display_name":"Gal Chechik","orcid":"https://orcid.org/0000-0001-9164-5303"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gal Chechik","raw_affiliation_strings":["Google Research","Google Research Mountain View, CA 94043, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research Mountain View, CA 94043, US","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100722234","display_name":"Chen Sun","orcid":"https://orcid.org/0000-0001-8772-9627"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Sun","raw_affiliation_strings":["Google Research","Google Research Mountain View, CA 94043, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research Mountain View, CA 94043, US","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053959119","display_name":"Bin Shen","orcid":"https://orcid.org/0000-0002-0167-3034"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bin Shen","raw_affiliation_strings":["Google Research","Google Research Mountain View, CA 94043, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Research","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research Mountain View, CA 94043, US","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1291425158"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.03769367,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2943","last_page":"2949"},"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":0.9980000257492065,"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":0.9980000257492065,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9976000189781189,"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/T11439","display_name":"Video Analysis and Summarization","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":0.6820008754730225},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6168203949928284},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5359047055244446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5200511813163757},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.5025460720062256},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.48464637994766235},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.48274463415145874},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4301300644874573},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3679349422454834},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36032092571258545},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2971338629722595},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23217493295669556},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.13812050223350525}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6820008754730225},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6168203949928284},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5359047055244446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5200511813163757},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.5025460720062256},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.48464637994766235},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.48274463415145874},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4301300644874573},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3679349422454834},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36032092571258545},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2971338629722595},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23217493295669556},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.13812050223350525},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2017/410","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/410","pdf_url":"https://www.ijcai.org/proceedings/2017/0410.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2017/410","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/410","pdf_url":"https://www.ijcai.org/proceedings/2017/0410.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2620982237.pdf","grobid_xml":"https://content.openalex.org/works/W2620982237.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W16827692","https://openalex.org/W90657816","https://openalex.org/W1479807131","https://openalex.org/W1630959083","https://openalex.org/W1840988445","https://openalex.org/W1869398109","https://openalex.org/W1879524907","https://openalex.org/W1969198379","https://openalex.org/W2004227778","https://openalex.org/W2010792435","https://openalex.org/W2011295372","https://openalex.org/W2038531878","https://openalex.org/W2076752034","https://openalex.org/W2098166271","https://openalex.org/W2098239572","https://openalex.org/W2104290444","https://openalex.org/W2108745803","https://openalex.org/W2110119381","https://openalex.org/W2121947440","https://openalex.org/W2123073303","https://openalex.org/W2132914434","https://openalex.org/W2133510502","https://openalex.org/W2136504847","https://openalex.org/W2152322845","https://openalex.org/W2154318594","https://openalex.org/W2154455818","https://openalex.org/W2163474322","https://openalex.org/W2164816523","https://openalex.org/W2166338096","https://openalex.org/W2166688141","https://openalex.org/W2211992430","https://openalex.org/W2293597654","https://openalex.org/W2294964890","https://openalex.org/W2342481274","https://openalex.org/W2530157984","https://openalex.org/W2566720494","https://openalex.org/W2997701990","https://openalex.org/W4206593589","https://openalex.org/W4361807594","https://openalex.org/W6604177601","https://openalex.org/W6653020993","https://openalex.org/W6675092554","https://openalex.org/W6678698120","https://openalex.org/W6684158799","https://openalex.org/W6684392622","https://openalex.org/W6728222056","https://openalex.org/W6790825729","https://openalex.org/W6791858558","https://openalex.org/W6863994431","https://openalex.org/W6864014924"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W2378211422","https://openalex.org/W4388145910","https://openalex.org/W2381570729","https://openalex.org/W1976205134","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W4248336175","https://openalex.org/W2031260042","https://openalex.org/W2032548952"],"abstract_inverted_index":{"Label":[0,90],"propagation":[1,22,97],"is":[2,45,103,148],"a":[3,18,25,87,123],"popular":[4],"semi-supervised":[5],"learning":[6],"technique":[7],"that":[8,32,38,94],"transfers":[9],"information":[10,79],"from":[11],"labeled":[12],"examples":[13,16,37],"to":[14,64,80],"unlabeled":[15],"through":[17],"graph.":[19,146],"Most":[20],"label":[21,96],"methods":[23],"construct":[24,122],"graph":[26,35,124],"based":[27,73,125,149],"on":[28,74,126,150,159],"example-to-example":[29],"similarity,":[30],"assuming":[31],"the":[33,81,111,133,136,140,145,164,167],"resulting":[34],"connects":[36],"share":[39],"similar":[40,60,66],"labels.":[41,83],"Unfortunately,":[42],"example-level":[43],"similarity":[44,128],"sometimes":[46],"badly":[47],"defined.":[48],"For":[49],"instance,":[50],"two":[51,55,160],"images":[52],"may":[53],"contain":[54],"different":[56],"objects,":[57],"but":[58],"have":[59],"overall":[61],"appearance":[62],"due":[63],"large":[65],"background.":[67],"In":[68],"this":[69],"case,":[70],"computing":[71],"similarities":[72],"whole-image":[75],"would":[76],"fail":[77],"propagating":[78],"right":[82],"This":[84],"paper":[85],"proposes":[86],"novel":[88],"Instance-Level":[89],"Propagation":[91],"(ILLP)":[92],"approach":[93,169],"integrates":[95],"with":[98],"multi-instance":[99],"learning.":[100],"Each":[101],"example":[102],"treated":[104],"as":[105,109],"containing":[106],"multiple":[107,118],"instances,":[108],"in":[110,144],"case":[112],"of":[113,117,166],"an":[114,151],"image":[115],"consisting":[116],"regions.":[119],"We":[120],"first":[121],"instance-level":[127],"and":[129,138],"then":[130],"simultaneously":[131],"identify":[132],"instances":[134,143],"carrying":[135],"labels":[137,141],"propagate":[139],"across":[142],"Optimization":[147],"iterative":[152],"Expectation":[153],"Maximization":[154],"(EM)":[155],"algorithm.":[156],"Experimental":[157],"results":[158],"benchmark":[161],"datasets":[162],"demonstrate":[163],"effectiveness":[165],"proposed":[168],"over":[170],"several":[171],"state-of-the-art":[172],"methods.":[173]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
