{"id":"https://openalex.org/W4416249601","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228450","title":"Pseudo Triplet Guided Few-shot Composed Image Retrieval","display_name":"Pseudo Triplet Guided Few-shot Composed Image Retrieval","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416249601","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228450"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228450","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","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/A5047212151","display_name":"Bohan Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bohan Hou","raw_affiliation_strings":["Shandong University,Department of Computer Science and Technology,Qingdao,China"],"affiliations":[{"raw_affiliation_string":"Shandong University,Department of Computer Science and Technology,Qingdao,China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032205250","display_name":"Haoqiang Lin","orcid":"https://orcid.org/0009-0000-5768-5467"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoqiang Lin","raw_affiliation_strings":["Shandong University,Department of Computer Science and Technology,Qingdao,China"],"affiliations":[{"raw_affiliation_string":"Shandong University,Department of Computer Science and Technology,Qingdao,China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030366151","display_name":"Haokun Wen","orcid":"https://orcid.org/0000-0003-0633-3722"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]},{"id":"https://openalex.org/I158809036","display_name":"Shenzhen Institute of Information Technology","ror":"https://ror.org/03wrf9427","country_code":"CN","type":"education","lineage":["https://openalex.org/I158809036"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haokun Wen","raw_affiliation_strings":["Harbin Institute of Technology (Shenzhen),School of Computer Science and Technology,Shenzhen,China"],"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology (Shenzhen),School of Computer Science and Technology,Shenzhen,China","institution_ids":["https://openalex.org/I158809036","https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100940320","display_name":"Meng Liu","orcid":"https://orcid.org/0000-0003-2175-4402"},"institutions":[{"id":"https://openalex.org/I44445938","display_name":"Shandong Jianzhu University","ror":"https://ror.org/01gbfax37","country_code":"CN","type":"education","lineage":["https://openalex.org/I44445938"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Liu","raw_affiliation_strings":["Shandong Jianzhu University,Department of Computer Science,Jinan,China"],"affiliations":[{"raw_affiliation_string":"Shandong Jianzhu University,Department of Computer Science,Jinan,China","institution_ids":["https://openalex.org/I44445938"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040666380","display_name":"Mingzhu Xu","orcid":"https://orcid.org/0000-0002-1492-0970"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingzhu Xu","raw_affiliation_strings":["Shandong University,School of Software,Jinan,China"],"affiliations":[{"raw_affiliation_string":"Shandong University,School of Software,Jinan,China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072768866","display_name":"Xuemeng Song","orcid":"https://orcid.org/0000-0002-5274-4197"},"institutions":[{"id":"https://openalex.org/I44445938","display_name":"Shandong Jianzhu University","ror":"https://ror.org/01gbfax37","country_code":"CN","type":"education","lineage":["https://openalex.org/I44445938"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuemeng Song","raw_affiliation_strings":["Shandong Jianzhu University,Department of Computer Science,Jinan,China"],"affiliations":[{"raw_affiliation_string":"Shandong Jianzhu University,Department of Computer Science,Jinan,China","institution_ids":["https://openalex.org/I44445938"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5047212151"],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34249094,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.534500002861023,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.534500002861023,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.1979999989271164,"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":0.15850000083446503,"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/generalization","display_name":"Generalization","score":0.631600022315979},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.6182000041007996},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5863999724388123},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5699999928474426},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5388000011444092},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4984000027179718},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.49779999256134033},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.4844000041484833}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7943999767303467},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6614999771118164},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.631600022315979},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.6182000041007996},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5863999724388123},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5699999928474426},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5388000011444092},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4984000027179718},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.49779999256134033},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.4844000041484833},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.47999998927116394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4666999876499176},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4406000077724457},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36899998784065247},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.35019999742507935},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.33739998936653137},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3237999975681305},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2700999975204468},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2648000121116638}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228450","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228450","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2138079527","https://openalex.org/W2798820905","https://openalex.org/W2897628926","https://openalex.org/W2905544595","https://openalex.org/W2963249562","https://openalex.org/W2963530300","https://openalex.org/W2971157635","https://openalex.org/W3119510203","https://openalex.org/W3155230099","https://openalex.org/W3172514680","https://openalex.org/W3176909828","https://openalex.org/W3203247393","https://openalex.org/W4226048133","https://openalex.org/W4230030242","https://openalex.org/W4243354998","https://openalex.org/W4292828970","https://openalex.org/W4312121894","https://openalex.org/W4313156423","https://openalex.org/W4382240042","https://openalex.org/W4384655960","https://openalex.org/W4386071700","https://openalex.org/W4386501573","https://openalex.org/W4390203954","https://openalex.org/W4390873539","https://openalex.org/W4390874196","https://openalex.org/W4393159265","https://openalex.org/W4394625619","https://openalex.org/W4395483878","https://openalex.org/W4400526206","https://openalex.org/W4415708388"],"related_works":[],"abstract_inverted_index":{"Composed":[0],"Image":[1],"Retrieval":[2],"(CIR)":[3],"is":[4,199],"a":[5,16,20,39,62,111,160,169,179],"challenging":[6,161,174,189],"task":[7,55],"that":[8],"aims":[9],"to":[10,37,71,137,148,191],"retrieve":[11],"the":[12,43,54,78,87,123,150,155,193],"target":[13],"image":[14,143],"with":[15,203],"multimodal":[17],"query,":[18],"i.e.,":[19],"reference":[21],"image,":[22],"and":[23,47,60,95,131,145,178,201,223,231],"its":[24,75],"complementary":[25],"modification":[26,171],"text.":[27],"As":[28],"previous":[29],"supervised":[30,206],"or":[31],"zero-shot":[32],"learning":[33],"paradigms":[34],"all":[35],"fail":[36],"strike":[38],"good":[40],"trade-off":[41],"between":[42],"model\u2019s":[44],"generalization":[45],"ability":[46],"retrieval":[48],"performance,":[49,77],"recent":[50],"researchers":[51],"have":[52],"introduced":[53],"of":[56,228],"few-shot":[57,117],"CIR":[58,92,101,118,163,207],"(FS-CIR)":[59],"proposed":[61],"textual":[63],"inversion-based":[64],"network":[65],"based":[66],"on":[67,86,216],"pretrained":[68],"CLIP":[69],"model":[70,93,102,194],"realize":[72],"it.":[73],"Despite":[74],"promising":[76],"approach":[79],"encounters":[80],"two":[81,107,214],"key":[82],"limitations:":[83],"simply":[84],"relying":[85],"few":[88],"annotated":[89],"samples":[90],"for":[91,100,186],"training":[94,98],"indiscriminately":[96],"selecting":[97],"triplets":[99,140,190],"fine-tuning.":[103,195],"To":[104],"address":[105],"these":[106],"limitations,":[108],"we":[109,126,158,167],"propose":[110,127,159],"novel":[112],"two-stage":[113],"pseudo":[114,133,139,170],"triplet":[115,134],"guided":[116],"scheme,":[119],"dubbed":[120],"PTG-FSCIR.":[121],"In":[122,154],"first":[124],"stage,":[125,157],"an":[128],"attentive":[129],"masking":[130],"captioning-based":[132],"generation":[135],"method,":[136,165],"construct":[138],"from":[141],"pure":[142],"data":[144],"use":[146],"them":[147],"fulfill":[149],"CIR-task":[151],"specific":[152],"pretraining.":[153],"second":[156],"triplet-based":[162],"fine-tuning":[164],"where":[166],"design":[168],"text-based":[172],"sample":[173],"score":[175],"estimation":[176],"strategy":[177,185],"robust":[180,188],"top":[181],"range-based":[182],"random":[183],"sampling":[184,187],"promote":[192],"Notably,":[196],"our":[197,211,235],"scheme":[198,212],"plug-and-play":[200],"compatible":[202],"any":[204],"existing":[205],"models.":[208],"We":[209],"test":[210],"across":[213],"backbones":[215],"three":[217],"public":[218],"datasets":[219],"(i.e.,":[220],"FashionIQ,":[221],"CIRR,":[222],"Birds-to-Words),":[224],"achieving":[225],"maximum":[226],"improvements":[227],"13.3%,":[229],"22.2%,":[230],"17.4%":[232],"respectively,":[233],"demonstrating":[234],"scheme\u2019s":[236],"efficacy.":[237]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-14T00:00:00"}
