{"id":"https://openalex.org/W4321485430","doi":"https://doi.org/10.1145/3539597.3570425","title":"Self-supervised Multi-view Disentanglement for Expansion of Visual Collections","display_name":"Self-supervised Multi-view Disentanglement for Expansion of Visual Collections","publication_year":2023,"publication_date":"2023-02-22","ids":{"openalex":"https://openalex.org/W4321485430","doi":"https://doi.org/10.1145/3539597.3570425"},"language":"en","primary_location":{"id":"doi:10.1145/3539597.3570425","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3539597.3570425","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3539597.3570425","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3539597.3570425","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041973252","display_name":"Nihal Jain","orcid":"https://orcid.org/0000-0002-1939-0278"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nihal Jain","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1939-0278","affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086111928","display_name":"Praneetha Vaddamanu","orcid":"https://orcid.org/0000-0003-4894-9517"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Praneetha Vaddamanu","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":"https://orcid.org/0000-0003-4894-9517","affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051903902","display_name":"Paridhi Maheshwari","orcid":"https://orcid.org/0000-0001-6831-9091"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paridhi Maheshwari","raw_affiliation_strings":["Stanford University, Stanford, CA, USA"],"raw_orcid":"https://orcid.org/0000-0001-6831-9091","affiliations":[{"raw_affiliation_string":"Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022536276","display_name":"Vishwa Vinay","orcid":"https://orcid.org/0000-0002-4043-9953"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vishwa Vinay","raw_affiliation_strings":["Adobe Research, Bangalore, India"],"raw_orcid":"https://orcid.org/0000-0002-4043-9953","affiliations":[{"raw_affiliation_string":"Adobe Research, Bangalore, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077902428","display_name":"Kuldeep Kulkarni","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kuldeep Kulkarni","raw_affiliation_strings":["Adobe Research, Bangalore, India"],"raw_orcid":"https://orcid.org/0000-0003-4681-8986","affiliations":[{"raw_affiliation_string":"Adobe Research, Bangalore, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2246,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.47487264,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"841","last_page":"849"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9998000264167786,"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":0.9958000183105469,"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":0.7693692445755005},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6949360370635986},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6492824554443359},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5905654430389404},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5766560435295105},{"id":"https://openalex.org/keywords/query-expansion","display_name":"Query expansion","score":0.5562611818313599},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5077658891677856},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48199954628944397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46222934126853943},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4287633001804352},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3664400577545166}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7693692445755005},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6949360370635986},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6492824554443359},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5905654430389404},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5766560435295105},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.5562611818313599},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5077658891677856},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48199954628944397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46222934126853943},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4287633001804352},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3664400577545166},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3539597.3570425","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3539597.3570425","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3539597.3570425","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3539597.3570425","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3539597.3570425","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3539597.3570425","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.46000000834465027,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4321485430.pdf","grobid_xml":"https://content.openalex.org/works/W4321485430.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W204268067","https://openalex.org/W1604621732","https://openalex.org/W1969469774","https://openalex.org/W2037098674","https://openalex.org/W2130660124","https://openalex.org/W2132314908","https://openalex.org/W2163605009","https://openalex.org/W2518116149","https://openalex.org/W2619383789","https://openalex.org/W2883672875","https://openalex.org/W2892816441","https://openalex.org/W2905544595","https://openalex.org/W2912374867","https://openalex.org/W2940824926","https://openalex.org/W2962837952","https://openalex.org/W2970231061","https://openalex.org/W3035902092","https://openalex.org/W3093051361","https://openalex.org/W3100388646","https://openalex.org/W3108655343","https://openalex.org/W3122451732","https://openalex.org/W3136640957","https://openalex.org/W3139419286","https://openalex.org/W3176890766","https://openalex.org/W4206671592"],"related_works":["https://openalex.org/W2560191017","https://openalex.org/W2348892528","https://openalex.org/W2014728371","https://openalex.org/W3194422352","https://openalex.org/W2397627326","https://openalex.org/W1981131819","https://openalex.org/W3008917487","https://openalex.org/W1982237068","https://openalex.org/W2367877683","https://openalex.org/W2375480909"],"abstract_inverted_index":{"Image":[0],"search":[1],"engines":[2],"enable":[3],"the":[4,18,36,106,119,145],"retrieval":[5,76,134],"of":[6,31,58,62,121,147],"images":[7,25,103,142],"relevant":[8],"to":[9,55,73,117],"a":[10,21,29,56,67,75,93,122,125,148],"query":[11,22,149],"image.":[12],"In":[13],"this":[14,89,114],"work,":[15],"we":[16,91,130],"consider":[17],"setting":[19],"where":[20],"for":[23,66,97,102],"similar":[24],"is":[26,72,109],"derived":[27],"from":[28,85],"collection":[30,123],"images.":[32],"For":[33],"visual":[34],"search,":[35],"similarity":[37],"measurements":[38],"may":[39],"be":[40,136],"made":[41],"along":[42],"multiple":[43,86],"axes,":[44],"or":[45],"views,":[46],"such":[47,104],"as":[48,124],"style":[49],"and":[50],"color.":[51],"We":[52,111],"assume":[53],"access":[54],"set":[57],"feature":[59],"extractors,":[60],"each":[61],"which":[63],"computes":[64],"representations":[65,84,101],"specific":[68],"view.":[69],"Our":[70],"objective":[71],"design":[74],"algorithm":[77],"that":[78,105,143],"effectively":[79],"combines":[80],"similarities":[81],"computed":[82],"over":[83,127],"views.":[87,128],"To":[88],"end,":[90],"propose":[92],"self-supervised":[94],"learning":[95],"method":[96],"extracting":[98],"disentangled":[99],"view-specific":[100],"inter-view":[107],"overlap":[108],"minimized.":[110],"show":[112,131],"how":[113,132],"allows":[115],"us":[116],"compute":[118],"intent":[120,146],"distribution":[126],"Finally,":[129],"effective":[133],"can":[135],"performed":[137],"by":[138],"prioritizing":[139],"candidate":[140],"expansion":[141],"match":[144],"collection.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}