{"id":"https://openalex.org/W4415536158","doi":"https://doi.org/10.1145/3746027.3755067","title":"Mitigating Long-tail Distribution in Oracle Bone Inscriptions: Dataset, Model, and Benchmark","display_name":"Mitigating Long-tail Distribution in Oracle Bone Inscriptions: Dataset, Model, and Benchmark","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415536158","doi":"https://doi.org/10.1145/3746027.3755067"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755067","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","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":null,"display_name":"Jinhao Li","orcid":"https://orcid.org/0009-0009-9679-5517"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhao Li","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0009-9679-5517","affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100603244","display_name":"Zijian Chen","orcid":"https://orcid.org/0000-0002-8502-4110"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zijian Chen","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8502-4110","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Runze Jiang","orcid":"https://orcid.org/0009-0007-7035-6810"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runze Jiang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0007-7035-6810","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028572860","display_name":"Tingzhu Chen","orcid":"https://orcid.org/0000-0002-3417-7782"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingzhu Chen","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-3417-7782","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063110936","display_name":"Changbo Wang","orcid":"https://orcid.org/0000-0001-8940-6418"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changbo Wang","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8940-6418","affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064168853","display_name":"Guangtao Zhai","orcid":"https://orcid.org/0000-0001-8165-9322"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangtao Zhai","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8165-9322","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.84709764,"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":"7729","last_page":"7738"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.996999979019165,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.996999979019165,"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/T11212","display_name":"Cultural Heritage Materials Analysis","score":0.9700000286102295,"subfield":{"id":"https://openalex.org/subfields/1204","display_name":"Archeology"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9632999897003174,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/glyph","display_name":"Glyph (data visualization)","score":0.9176999926567078},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5404999852180481},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5109999775886536},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.46160000562667847},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4498000144958496},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4115999937057495},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.40790000557899475}],"concepts":[{"id":"https://openalex.org/C142816647","wikidata":"https://www.wikidata.org/wiki/Q5573018","display_name":"Glyph (data visualization)","level":3,"score":0.9176999926567078},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.753600001335144},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5404999852180481},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5109999775886536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4934000074863434},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.46160000562667847},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4498000144958496},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4115999937057495},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.40790000557899475},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3926999866962433},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.36079999804496765},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33899998664855957},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.31139999628067017},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.290800005197525},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.27630001306533813}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755067","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3755067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2064076387","https://openalex.org/W2127271787","https://openalex.org/W2962785568","https://openalex.org/W2962793481","https://openalex.org/W3004249119","https://openalex.org/W3173217100","https://openalex.org/W4223975244","https://openalex.org/W4225672218","https://openalex.org/W4225690778","https://openalex.org/W4286238648","https://openalex.org/W4287831878","https://openalex.org/W4290927878","https://openalex.org/W4304080282","https://openalex.org/W4312812783","https://openalex.org/W4312933868","https://openalex.org/W4328136562","https://openalex.org/W4385961571","https://openalex.org/W4387967877","https://openalex.org/W4389235843","https://openalex.org/W4390873054","https://openalex.org/W4390978328","https://openalex.org/W4399435533"],"related_works":[],"abstract_inverted_index":{"The":[0,185],"oracle":[1],"bone":[2],"inscription":[3],"(OBI)":[4],"recognition":[5,36],"plays":[6],"a":[7,26,55,88,111,127,132],"significant":[8],"role":[9],"in":[10,46],"understanding":[11],"the":[12,20,60,86,140,144,148,162,165],"history":[13],"and":[14,40,95,122,131,157,169,188],"culture":[15],"of":[16,34,63,98,143,164],"ancient":[17],"China.":[18],"However,":[19],"existing":[21],"OBI":[22,35,49,68,90,93,106,115,124,154],"datasets":[23,69],"suffer":[24],"from":[25,105],"long-tail":[27],"distribution":[28],"problem,":[29],"leading":[30],"to":[31,58,119,147],"biased":[32],"performance":[33],"models":[37,190],"across":[38],"majority":[39],"minority":[41,64],"classes.":[42,65],"With":[43],"recent":[44],"advancements":[45],"generative":[47,76],"models,":[48],"synthesis-based":[50],"data":[51],"augmentation":[52],"has":[53],"become":[54],"promising":[56],"avenue":[57],"expand":[59],"sample":[61],"size":[62],"Unfortunately,":[66],"current":[67],"lack":[70],"large-scale":[71],"structure-aligned":[72,89],"image":[73,130],"pairs":[74],"for":[75,92],"model":[77],"training.":[78],"To":[79],"address":[80],"these":[81],"problems,":[82],"we":[83,109],"first":[84],"present":[85],"Oracle-P15K,":[87],"dataset":[91,168],"generation":[94],"denoising,":[96],"consisting":[97],"14,542":[99],"images":[100],"infused":[101],"with":[102],"domain":[103],"knowledge":[104],"experts.":[107],"Second,":[108],"propose":[110],"diffusion":[112],"model-based":[113],"pseudo":[114],"generator,":[116],"called":[117],"OBIDiff,":[118],"achieve":[120],"realistic":[121],"controllable":[123],"generation.":[125],"Given":[126],"clean":[128],"glyph":[129,149,177],"target":[133],"rubbing-style":[134],"image,":[135],"it":[136],"can":[137,173],"effectively":[138],"transfer":[139],"noise":[141],"style":[142],"original":[145],"rubbing":[146,182],"image.":[150],"Extensive":[151],"experiments":[152],"on":[153],"downstream":[155],"tasks":[156],"user":[158],"preference":[159],"studies":[160],"show":[161],"effectiveness":[163],"proposed":[166],"Oracle-P15K":[167],"demonstrate":[170],"that":[171],"OBIDiff":[172],"accurately":[174],"preserve":[175],"inherent":[176],"structures":[178],"while":[179],"transferring":[180],"authentic":[181],"styles":[183],"effectively.":[184],"dataset,":[186],"code,":[187],"pre-trained":[189],"are":[191],"available":[192],"at":[193],"https://github.com/LJHolyGround/Oracle-P15K.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-25T00:00:00"}
