{"id":"https://openalex.org/W7138033058","doi":"https://doi.org/10.1609/aaai.v40i7.37432","title":"Less Is Better: Sparse Instance Learning for Cross-Domain Few-Shot Object Detection","display_name":"Less Is Better: Sparse Instance Learning for Cross-Domain Few-Shot Object Detection","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138033058","doi":"https://doi.org/10.1609/aaai.v40i7.37432"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i7.37432","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i7.37432","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i7.37432","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129732762","display_name":"Yali Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yali Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129659546","display_name":"Jie Mei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jie Mei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129712852","display_name":"Ziyi Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ziyi Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129657627","display_name":"Yiming Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yiming Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129740820","display_name":"Hongru Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongru Zhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017257056","display_name":"Mingyuan Jiu","orcid":"https://orcid.org/0000-0002-4868-0709"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mingyuan Jiu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5029896607","display_name":"Hichem Sahbi","orcid":"https://orcid.org/0000-0001-6813-9146"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hichem Sahbi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23124406,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"7","first_page":"5176","last_page":"5184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.6651999950408936,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.6651999950408936,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.2948000133037567,"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":0.0052999998442828655,"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/discriminative-model","display_name":"Discriminative model","score":0.7562999725341797},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6708999872207642},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6651999950408936},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5562000274658203},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.542900025844574},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5195000171661377},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5170000195503235},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4449000060558319},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4242999851703644},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.3864000141620636}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7842000126838684},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7562999725341797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7003999948501587},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6708999872207642},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6651999950408936},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5562000274658203},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.542900025844574},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5195000171661377},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5170000195503235},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4449000060558319},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4242999851703644},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3864000141620636},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.38609999418258667},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.36899998784065247},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36640000343322754},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C182521987","wikidata":"https://www.wikidata.org/wiki/Q2493877","display_name":"Viola\u2013Jones object detection framework","level":5,"score":0.3375000059604645},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3328000009059906},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3327000141143799},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.3294999897480011},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.3116999864578247},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2842000126838684},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.2759999930858612},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.26809999346733093},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2669000029563904},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.2630000114440918},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2614000141620636},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.25440001487731934}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i7.37432","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i7.37432","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/37432","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/37432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i7.37432","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i7.37432","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.763327956199646,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Cross-Domain":[0],"Few-Shot":[1],"Object":[2],"Detection":[3],"(CD-FSOD)":[4],"is":[5,126],"an":[6],"extremely":[7],"challenging":[8],"task":[9],"due":[10],"to":[11,67,105,113,129,138],"the":[12,21,38,45,89,96,103,132,152],"inherent":[13],"data":[14],"scarcity":[15],"and":[16,23,32,111],"substantial":[17],"domain":[18],"shift":[19],"between":[20],"source":[22],"target":[24,46],"domains.":[25],"Existing":[26],"methods":[27],"often":[28],"suffer":[29],"from":[30],"overfitting":[31],"noisy":[33,118],"feature":[34,84],"representations,":[35],"which":[36,63],"hinder":[37],"construction":[39],"of":[40,82],"discriminative":[41,158],"class":[42,133],"prototypes":[43,134],"in":[44],"domain.":[47],"In":[48],"this":[49],"paper,":[50],"we":[51],"propose":[52],"a":[53,69,77,121],"novel":[54],"framework":[55],"with":[56,72,135],"sparse":[57],"instance":[58,65,83],"learning":[59],"(SI-ViTO)":[60],"for":[61],"CD-FSOD,":[62],"leverages":[64],"sparsity":[66,79,85,101],"achieve":[68],"better":[70,161],"detection":[71,165],"less":[73,157],"representation.":[74],"SI-ViTO":[75,150],"adopts":[76],"dual-stage":[78],"module,":[80],"consisting":[81],"not":[86],"only":[87],"on":[88,95,145],"few-shot":[90,163],"support":[91],"images":[92],"but":[93],"also":[94,127],"query":[97,136],"images.":[98],"This":[99],"dual":[100],"enables":[102],"model":[104],"effectively":[106],"preserve":[107],"salient":[108],"foreground":[109],"semantics":[110],"simultaneously":[112],"filter":[114],"out":[115],"redundant":[116],"or":[117],"information.":[119],"Furthermore,":[120],"new":[122],"prototype":[123,140],"calibration":[124],"strategy":[125],"used":[128],"dynamically":[130],"refine":[131],"instances":[137],"accelerate":[139],"adaptation.":[141],"Extensive":[142],"experimental":[143],"results":[144],"CD-FSOD":[146],"benchmarks":[147],"show":[148],"that":[149,156],"outperforms":[151],"state-of-the-art":[153],"methods,":[154],"demonstrating":[155],"representations":[159],"yield":[160],"cross-domain":[162],"object":[164],"performance":[166],"than":[167],"more":[168],"abundant":[169],"ones.":[170]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-18T00:00:00"}
