{"id":"https://openalex.org/W7167049325","doi":"https://doi.org/10.48550/arxiv.2607.00338","title":"DroneFINE: Domain-Aware Parameter-Efficient Fine-Tuning of Vision-Language Detectors for Drone Images","display_name":"DroneFINE: Domain-Aware Parameter-Efficient Fine-Tuning of Vision-Language Detectors for Drone Images","publication_year":2026,"publication_date":"2026-07-01","ids":{"openalex":"https://openalex.org/W7167049325","doi":"https://doi.org/10.48550/arxiv.2607.00338"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.00338","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00338","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.00338","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139928637","display_name":"Ke Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Ke","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139879598","display_name":"Yanan Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yanan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139926023","display_name":"Yingjie Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gao, Yingjie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139927890","display_name":"Wenhao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Wenhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139943237","display_name":"Chenyu Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Chenyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139928923","display_name":"XinZhu Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, XinZhu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139892112","display_name":"Jiaxin Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jiaxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139857647","display_name":"Di Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Di","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.46399998664855957,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.46399998664855957,"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":0.36550000309944153,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.08110000193119049,"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/drone","display_name":"Drone","score":0.7833999991416931},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.6021000146865845},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6019999980926514},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5041000247001648},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4505999982357025},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43799999356269836},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.38659998774528503},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.35679998993873596},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.34209999442100525}],"concepts":[{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.7833999991416931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7580000162124634},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6919999718666077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6528000235557556},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.6021000146865845},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6019999980926514},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5041000247001648},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4505999982357025},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43799999356269836},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.38659998774528503},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.35679998993873596},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.34209999442100525},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.32690000534057617},{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.30809998512268066},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2946000099182129},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C2779199153","wikidata":"https://www.wikidata.org/wiki/Q43965","display_name":"Quadcopter","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.26510000228881836},{"id":"https://openalex.org/C2987819851","wikidata":"https://www.wikidata.org/wiki/Q191839","display_name":"Aerial imagery","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2556000053882599}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.00338","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00338","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.00338","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00338","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Object":[0],"detection":[1],"for":[2,27,96],"Unmanned":[3],"Aerial":[4],"Vehicles":[5],"(UAVs)":[6],"working":[7],"in":[8,59,146],"open":[9],"and":[10,48,105,156,166],"dynamic":[11],"environments":[12],"is":[13,111,129,132],"a":[14,24,40,86,102,123,133],"highly":[15],"challenging":[16],"task.":[17],"While":[18],"Vision-Language":[19],"Models":[20],"(VLMs)":[21],"have":[22],"offered":[23],"powerful":[25],"solution":[26],"universal":[28],"object":[29],"detection,":[30],"adapting":[31],"them":[32],"to":[33,39,141,170],"UAV":[34,77],"scenarios":[35],"remains":[36],"non-trivial":[37],"due":[38],"substantial":[41],"domain":[42],"gap":[43],"between":[44],"VLM":[45],"pre-training":[46],"data":[47],"aerial":[49],"imagery.":[50],"The":[51],"prevailing":[52],"Parameter-Efficient":[53],"Fine-Tuning":[54],"(PEFT)":[55],"methods":[56,165],"prove":[57],"ineffective":[58],"bridging":[60],"this":[61,81],"gap,":[62],"as":[63],"VLMs'":[64],"\"natural-scene,":[65],"foreground-dominant\"":[66],"visual":[67],"priors":[68],"misalign":[69],"with":[70],"the":[71,115,144,176],"\"bird's-eye-view,":[72],"background-dominant,":[73],"small-object\"":[74],"characteristics":[75],"of":[76,119,178],"data.":[78],"To":[79],"address":[80],"issue,":[82],"we":[83],"propose":[84],"DroneFINE,":[85],"novel":[87],"PEFT":[88,164],"paradigm":[89],"comprising":[90],"two":[91],"domain-aware":[92],"complementary":[93],"modules":[94],"tailored":[95],"VLM-based":[97],"drone":[98],"image":[99],"detectors.":[100],"Specifically,":[101],"data-dependent,":[103],"foreground-aware,":[104],"multi-path":[106],"adaptation":[107],"mechanism":[108],"named":[109,127],"HyperAdapter":[110],"designed,":[112],"which":[113],"overcomes":[114],"static":[116],"structural":[117],"constraints":[118],"PEFT.":[120],"In":[121],"addition,":[122],"background":[124,139],"suppression":[125],"algorithm":[126],"SemanticGate":[128],"developed.":[130],"It":[131],"text-conditioned":[134],"guidance":[135],"strategy":[136],"that":[137,159],"employs":[138],"vocabulary":[140],"actively":[142],"guide":[143],"model":[145],"suppressing":[147],"responses":[148],"from":[149],"irrelevant":[150],"regions.":[151],"Extensive":[152],"experiments":[153],"on":[154],"VisDrone":[155],"UAVDT":[157],"demonstrate":[158],"DroneFINE":[160],"significantly":[161],"outperforms":[162],"existing":[163],"achieves":[167],"performance":[168],"comparable":[169],"full":[171],"fine-tuning":[172],"while":[173],"substantially":[174],"reducing":[175],"number":[177],"trainable":[179],"parameters.":[180]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-03T00:00:00"}