{"id":"https://openalex.org/W4410616214","doi":"https://doi.org/10.1109/tpami.2025.3572476","title":"Benchmarking and Analyzing Generative Data for Visual Recognition","display_name":"Benchmarking and Analyzing Generative Data for Visual Recognition","publication_year":2025,"publication_date":"2025-05-22","ids":{"openalex":"https://openalex.org/W4410616214","doi":"https://doi.org/10.1109/tpami.2025.3572476","pmid":"https://pubmed.ncbi.nlm.nih.gov/40402710"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3572476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3572476","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Bo Li","orcid":"https://orcid.org/0000-0002-8447-0928"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Bo Li","raw_affiliation_strings":["S-Lab, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-8447-0928","affiliations":[{"raw_affiliation_string":"S-Lab, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Haotian Liu","orcid":"https://orcid.org/0000-0002-5822-7385"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haotian Liu","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, WI, USA","University of Wisconsin-Madison, USA"],"raw_orcid":"https://orcid.org/0000-0002-5822-7385","affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]},{"raw_affiliation_string":"University of Wisconsin-Madison, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Liangyu Chen","orcid":"https://orcid.org/0000-0002-5181-8457"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Liangyu Chen","raw_affiliation_strings":["S-Lab, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-5181-8457","affiliations":[{"raw_affiliation_string":"S-Lab, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yong Jae Lee","orcid":"https://orcid.org/0000-0001-9863-1270"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yong Jae Lee","raw_affiliation_strings":["University of Wisconsin-Madison, Madison, WI, USA","University of Wisconsin-Madison, USA"],"raw_orcid":"https://orcid.org/0000-0001-9863-1270","affiliations":[{"raw_affiliation_string":"University of Wisconsin-Madison, Madison, WI, USA","institution_ids":["https://openalex.org/I135310074"]},{"raw_affiliation_string":"University of Wisconsin-Madison, USA","institution_ids":["https://openalex.org/I135310074"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107893340","display_name":"Chunyuan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chunyuan Li","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA","Microsoft Research, Redmond, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft Research, Redmond, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ziwei Liu","orcid":"https://orcid.org/0000-0002-4220-5958"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ziwei Liu","raw_affiliation_strings":["S-Lab, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-4220-5958","affiliations":[{"raw_affiliation_string":"S-Lab, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04997107,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"47","issue":"9","first_page":"7675","last_page":"7688"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.59170001745224,"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/T10320","display_name":"Neural Networks and Applications","score":0.59170001745224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.8326276540756226},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7101662158966064},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6487467288970947},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5092036128044128},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.48668938875198364},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4610447585582733},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37271255254745483},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3240189552307129}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8326276540756226},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7101662158966064},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6487467288970947},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5092036128044128},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.48668938875198364},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4610447585582733},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37271255254745483},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3240189552307129},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2025.3572476","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3572476","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:40402710","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40402710","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W12634471","https://openalex.org/W764651262","https://openalex.org/W1977295328","https://openalex.org/W2017814585","https://openalex.org/W2031489346","https://openalex.org/W2047643928","https://openalex.org/W2112796928","https://openalex.org/W2117539524","https://openalex.org/W2117876524","https://openalex.org/W2138011018","https://openalex.org/W2155904486","https://openalex.org/W2167222293","https://openalex.org/W2487365028","https://openalex.org/W2533598788","https://openalex.org/W2592962403","https://openalex.org/W2806857275","https://openalex.org/W2964194231","https://openalex.org/W2970986510","https://openalex.org/W2998385486","https://openalex.org/W3011199201","https://openalex.org/W3096831136","https://openalex.org/W3139224848","https://openalex.org/W3172845486","https://openalex.org/W3199693760","https://openalex.org/W3207539211","https://openalex.org/W4312920106","https://openalex.org/W4312933868","https://openalex.org/W4385573236","https://openalex.org/W4385801086","https://openalex.org/W4386057720","https://openalex.org/W4386076027","https://openalex.org/W4390873054","https://openalex.org/W6638677478","https://openalex.org/W6679045638","https://openalex.org/W6713645886","https://openalex.org/W6746171285","https://openalex.org/W6755207826","https://openalex.org/W6755312952","https://openalex.org/W6769627184","https://openalex.org/W6770813465","https://openalex.org/W6774222543","https://openalex.org/W6774908330","https://openalex.org/W6776929863","https://openalex.org/W6777615688","https://openalex.org/W6779823529","https://openalex.org/W6783713337","https://openalex.org/W6787972765","https://openalex.org/W6788990321","https://openalex.org/W6791353385","https://openalex.org/W6796042156","https://openalex.org/W6796581206","https://openalex.org/W6797053846","https://openalex.org/W6809885388","https://openalex.org/W6810039040","https://openalex.org/W6810730852","https://openalex.org/W6810940779","https://openalex.org/W6838639034","https://openalex.org/W6841755765","https://openalex.org/W6844872470","https://openalex.org/W6845839425","https://openalex.org/W6845868278","https://openalex.org/W6847062943","https://openalex.org/W6849177959","https://openalex.org/W6849592357"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2000169967","https://openalex.org/W2112883198"],"abstract_inverted_index":{"Advancements":[0],"in":[1,14,162],"large":[2],"pre-trained":[3],"generative":[4,24,34,60,93,107,124,159],"models":[5],"have":[6],"expanded":[7],"their":[8],"potential":[9],"as":[10],"effective":[11],"data":[12,32,61,108,111],"generators":[13],"visual":[15,64,163],"recognition.":[16],"This":[17],"work":[18],"delves":[19],"into":[20],"the":[21,72,113,120],"impact":[22],"of":[23,75,106,123],"images,":[25],"primarily":[26],"comparing":[27],"paradigms":[28],"that":[29],"harness":[30],"external":[31,115],"(i.e.":[33],"vs.":[35,37],"retrieval":[36],"original).":[38],"Our":[39,153],"key":[40,167],"contributions":[41],"are:":[42],"1)":[43],"GenBench":[44],"Construction:":[45],"We":[46],"devise":[47],"GenBench,":[48],"a":[49,89],"broad":[50],"benchmark":[51,155],"comprising":[52],"22":[53],"datasets":[54],"with":[55,82,109,149],"2548":[56],"categories,":[57],"to":[58,100,118],"appraise":[59],"across":[62,143],"various":[63],"recognition":[65,84,97],"tasks.":[66],"2)":[67],"CLER":[68],"Score:":[69],"To":[70],"address":[71],"insufficient":[73],"correlation":[74],"existing":[76],"metrics":[77],"(e.g.,":[78],"FID,":[79],"CLIP":[80],"score)":[81],"downstream":[83],"performance,":[85],"we":[86],"propose":[87],"CLER,":[88],"training-free":[90],"metric":[91],"indicating":[92],"data's":[94,160],"efficiency":[95],"for":[96,135,169],"tasks":[98],"prior":[99],"training.":[101],"3)":[102],"New":[103],"Baselines:":[104],"Comparisons":[105],"retrieved":[110],"from":[112],"same":[114],"pool":[116],"help":[117],"elucidate":[119],"unique":[121],"traits":[122],"data.":[125],"4)":[126],"External":[127],"Knowledge":[128],"Injection:":[129],"By":[130],"fine-tuning":[131],"special":[132],"token":[133],"embeddings":[134],"each":[136],"category":[137],"via":[138],"Textual":[139],"Inversion,":[140],"performance":[141],"improves":[142],"17":[144],"datasets,":[145],"except":[146],"when":[147],"dealing":[148],"low-resolution":[150],"reference":[151],"images.":[152],"exhaustive":[154],"and":[156],"analysis":[157],"spotlight":[158],"promise":[161],"recognition,":[164],"while":[165],"identifying":[166],"challenges":[168],"future":[170],"investigation.":[171]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
