{"id":"https://openalex.org/W4413017828","doi":"https://doi.org/10.1109/iv64158.2025.11097819","title":"Subset Selection for Autonomous Driving Datasets via Fine-Tuning Vision Foundation Models","display_name":"Subset Selection for Autonomous Driving Datasets via Fine-Tuning Vision Foundation Models","publication_year":2025,"publication_date":"2025-06-22","ids":{"openalex":"https://openalex.org/W4413017828","doi":"https://doi.org/10.1109/iv64158.2025.11097819"},"language":"en","primary_location":{"id":"doi:10.1109/iv64158.2025.11097819","doi":"https://doi.org/10.1109/iv64158.2025.11097819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv64158.2025.11097819","pdf_url":null,"source":{"id":"https://openalex.org/S4210198592","display_name":"IEEE Intelligent Vehicles Symposium","issn_l":"1931-0587","issn":["1931-0587","2642-7214"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"parent_works":[],"lineage":["https://openalex.org/W4413017828"],"child_works_count":0,"type":"conference-paper","is_traditional":true,"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/A5054710951","display_name":"Mert Keser","orcid":"https://orcid.org/0000-0001-7373-437X","observed_orcids":["https://orcid.org/0000-0001-7373-437X"]},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mert Keser","raw_affiliation_strings":["Technical University of Munich,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich,Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120391960","display_name":"Sinan Simsek","orcid":"https://orcid.org/0000-0002-9650-3846","observed_orcids":["https://orcid.org/0000-0002-9650-3846"]},"institutions":[{"id":"https://openalex.org/I188740104","display_name":"Ba\u015fkent University","ror":"https://ror.org/02v9bqx10","country_code":"TR","type":"education","lineage":["https://openalex.org/I188740104"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Sinan Simsek","raw_affiliation_strings":["Baskent University,Turkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baskent University,Turkiye","institution_ids":["https://openalex.org/I188740104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006962069","display_name":"Deniz Karacor","orcid":"https://orcid.org/0000-0001-6961-8966","observed_orcids":["https://orcid.org/0000-0001-6961-8966"]},"institutions":[{"id":"https://openalex.org/I188740104","display_name":"Ba\u015fkent University","ror":"https://ror.org/02v9bqx10","country_code":"TR","type":"education","lineage":["https://openalex.org/I188740104"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Deniz Karacor","raw_affiliation_strings":["Baskent University,Turkiye"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baskent University,Turkiye","institution_ids":["https://openalex.org/I188740104"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063781430","display_name":"Alois Knoll","orcid":"https://orcid.org/0000-0003-4840-076X","observed_orcids":["https://orcid.org/0000-0003-4840-076X"]},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alois Knoll","raw_affiliation_strings":["Technical University of Munich,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Munich,Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"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":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2251","last_page":"2258"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.513700008392334,"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":0.513700008392334,"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":0.39820000529289246,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.07919999957084656,"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/autonomous-driving-datasets","display_name":"autonomous driving datasets","score":0.7089999914169312},{"id":"https://openalex.org/keywords/data-curation","display_name":"data curation","score":0.7900000214576721},{"id":"https://openalex.org/keywords/vision-foundation-models","display_name":"vision foundation models","score":0.9449999928474426},{"id":"https://openalex.org/keywords/contrastive-learning","display_name":"contrastive learning","score":0.8330000042915344},{"id":"https://openalex.org/keywords/density-based-clustering","display_name":"density-based clustering","score":0.9350000023841858},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"semantic segmentation","score":0.652999997138977},{"id":"https://openalex.org/keywords/sample-selection","display_name":"sample selection","score":0.47200000286102295},{"id":"https://openalex.org/keywords/annotation-cost-reduction","display_name":"annotation cost reduction","score":0.5839999914169312}],"concepts":[{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6798657178878784},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.6741799712181091},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6326003074645996},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5124014019966125},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3586500287055969},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09879180788993835},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv64158.2025.11097819","doi":"https://doi.org/10.1109/iv64158.2025.11097819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv64158.2025.11097819","pdf_url":null,"source":{"id":"https://openalex.org/S4210198592","display_name":"IEEE Intelligent Vehicles Symposium","issn_l":"1931-0587","issn":["1931-0587","2642-7214"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","norway-1"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.4000000059604645}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1912128066","https://openalex.org/W2038827046","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2542065864","https://openalex.org/W2740924709","https://openalex.org/W2769342702","https://openalex.org/W2774918944","https://openalex.org/W2953303875","https://openalex.org/W2963041685","https://openalex.org/W2964309882","https://openalex.org/W2992046967","https://openalex.org/W3011249019","https://openalex.org/W3094502228","https://openalex.org/W3112288498","https://openalex.org/W3128343487","https://openalex.org/W3134385809","https://openalex.org/W3135367836","https://openalex.org/W3159481202","https://openalex.org/W3164803610","https://openalex.org/W4292121845","https://openalex.org/W4313678530","https://openalex.org/W4379539926","https://openalex.org/W4382141971","https://openalex.org/W4387495995","https://openalex.org/W4390874575","https://openalex.org/W4391769014","https://openalex.org/W4392172801","https://openalex.org/W4393159587","https://openalex.org/W4396214375","https://openalex.org/W4396869735","https://openalex.org/W4396982312","https://openalex.org/W4401416113","https://openalex.org/W4402696041","https://openalex.org/W4404569655","https://openalex.org/W4404612908","https://openalex.org/W4406208390","https://openalex.org/W4406449691","https://openalex.org/W4407981605","https://openalex.org/W4408793724","https://openalex.org/W6762585180","https://openalex.org/W6851800889","https://openalex.org/W6857622040","https://openalex.org/W7133187703"],"related_works":["https://openalex.org/W4415914379","https://openalex.org/W3015034699","https://openalex.org/W3204367575","https://openalex.org/W4415143615","https://openalex.org/W3138257668","https://openalex.org/W3126015239","https://openalex.org/W4402754221","https://openalex.org/W2799352588","https://openalex.org/W7217151948","https://openalex.org/W3143733707"],"abstract_inverted_index":{"Training":[0],"large-scale":[1],"vision":[2,43,66],"models":[3,45,102],"for":[4],"autonomous":[5],"driving":[6],"is":[7],"computationally":[8],"expensive":[9],"and":[10,48,108,124,145],"requires":[11],"extensive":[12],"manual":[13],"annotation.":[14],"While":[15],"reducing":[16],"dataset":[17,55,131],"size":[18],"could":[19],"address":[20],"these":[21],"limitations,":[22],"it":[23],"typically":[24],"results":[25,134],"in":[26,76,112],"degraded":[27],"model":[28,122],"performance.":[29,59],"In":[30],"this":[31],"paper,":[32],"we":[33,93],"propose":[34],"a":[35,63,69,149],"novel":[36],"self-supervised":[37,137],"data":[38,138],"selection":[39,111,139],"framework":[40],"that":[41,86,95,136],"leverages":[42],"foundation":[44,64,121],"to":[46,81,152],"identify":[47],"retain":[49,82],"high-value":[50],"training":[51,96],"samples,":[52],"enabling":[53],"efficient":[54],"curation":[56],"without":[57],"compromising":[58],"Our":[60,133],"approach":[61],"fine-tunes":[62],"model's":[65],"encoder":[67],"using":[68],"contrastive":[70],"objective,":[71],"then":[72],"perform":[73],"density-based":[74],"clustering":[75],"its":[77],"learned":[78],"embedding":[79],"space":[80],"only":[83],"those":[84],"samples":[85],"maximally":[87],"preserve":[88],"semantic":[89,113],"diversity.":[90],"Through":[91],"experiments,":[92],"show":[94],"on":[97,104],"our":[98,117],"curated":[99],"subset":[100],"outperforms":[101],"trained":[103],"the":[105],"full":[106],"dataset,":[107],"exceeds":[109],"random":[110],"segmentation":[114,125],"tasks.":[115],"Additionally,":[116],"comparisons":[118],"across":[119],"different":[120],"architectures":[123],"backbones":[126],"provide":[127],"insights":[128],"into":[129],"effective":[130],"curation.":[132],"highlight":[135],"can":[140],"significantly":[141],"reduce":[142],"both":[143],"annotation":[144],"computational":[146],"overhead,":[147],"providing":[148],"scalable":[150],"alternative":[151],"naively":[153],"expanding":[154],"datasets.":[155]},"counts_by_year":[],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}