{"id":"https://openalex.org/W7160318977","doi":"https://doi.org/10.1109/wacv61042.2026.00405","title":"Decomposition Sampling for Efficient Region Annotations in Active Learning","display_name":"Decomposition Sampling for Efficient Region Annotations in Active Learning","publication_year":2026,"publication_date":"2026-03-06","ids":{"openalex":"https://openalex.org/W7160318977","doi":"https://doi.org/10.1109/wacv61042.2026.00405"},"language":null,"primary_location":{"id":"doi:10.1109/wacv61042.2026.00405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00405","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","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":"https://openalex.org/A5135321122","display_name":"Jingna Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jingna Qiu","raw_affiliation_strings":["Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057284684","display_name":"Frauke Wilm","orcid":"https://orcid.org/0000-0002-9065-0554"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Frauke Wilm","raw_affiliation_strings":["Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016137375","display_name":"Mathias \u00d6ttl","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Mathias \u00d6ttl","raw_affiliation_strings":["Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020455437","display_name":"Jonas Utz","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jonas Utz","raw_affiliation_strings":["Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032420382","display_name":"Maja Schlereth","orcid":"https://orcid.org/0009-0003-4418-7065"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maja Schlereth","raw_affiliation_strings":["Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066469547","display_name":"Moritz Schillinger","orcid":"https://orcid.org/0009-0008-3506-6719"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Moritz Schillinger","raw_affiliation_strings":["Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universit&#x00E4;t Erlangen-N&#x00FC;rnberg","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018481044","display_name":"Marc Aubreville","orcid":"https://orcid.org/0000-0002-5294-5247"},"institutions":[{"id":"https://openalex.org/I88713005","display_name":"Flensburg University of Applied Sciences","ror":"https://ror.org/01xpfrc74","country_code":"DE","type":"education","lineage":["https://openalex.org/I88713005"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marc Aubreville","raw_affiliation_strings":["Hochschule Flensburg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hochschule Flensburg","institution_ids":["https://openalex.org/I88713005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025681380","display_name":"Katharina Breininger","orcid":"https://orcid.org/0000-0001-7600-5869"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Katharina Breininger","raw_affiliation_strings":["Julius-Maximilians-Universit&#x00E4;t W&#x00FC;rzburg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Julius-Maximilians-Universit&#x00E4;t W&#x00FC;rzburg","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"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":0.46060751,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4160","last_page":"4169"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9939000010490417,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9939000010490417,"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":0.0010000000474974513,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.000699999975040555,"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/active-learning","display_name":"Active learning (machine learning)","score":0.617900013923645},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4885999858379364},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.37389999628067017},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.29280000925064087},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.2874999940395355}],"concepts":[{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.617900013923645},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5921000242233276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5478000044822693},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4885999858379364},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.37389999628067017},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3165000081062317},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31029999256134033},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2669000029563904}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv61042.2026.00405","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv61042.2026.00405","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1978633512","https://openalex.org/W2148309496","https://openalex.org/W2340897893","https://openalex.org/W2625559849","https://openalex.org/W2798820905","https://openalex.org/W2805886241","https://openalex.org/W2884822772","https://openalex.org/W2904204744","https://openalex.org/W2956371155","https://openalex.org/W2977942577","https://openalex.org/W2978442853","https://openalex.org/W2989722562","https://openalex.org/W3014974815","https://openalex.org/W3090605478","https://openalex.org/W3195117579","https://openalex.org/W3209367260","https://openalex.org/W3214733388","https://openalex.org/W4291325848","https://openalex.org/W4297324618","https://openalex.org/W4307090174","https://openalex.org/W4312694520","https://openalex.org/W4322765902","https://openalex.org/W4385071532","https://openalex.org/W4386076222","https://openalex.org/W4386536409","https://openalex.org/W4387226220","https://openalex.org/W7133229362"],"related_works":[],"abstract_inverted_index":{"Active":[0],"learning":[1,96],"improves":[2],"annotation":[3,12,50,60,69,105],"efficiency":[4],"by":[5,107,149],"selecting":[6,23],"the":[7,31,126],"most":[8,17],"informative":[9,24],"samples":[10],"for":[11,26,61,67],"and":[13,43,76,82,115,141,154],"model":[14],"training.":[15],"While":[16],"prior":[18],"work":[19],"has":[20,51],"focused":[21],"on":[22,85,157],"images":[25,109],"classification":[27],"tasks,":[28],"we":[29],"investigate":[30],"more":[32,41,56],"challenging":[33,159],"setting":[34],"of":[35],"dense":[36],"prediction,":[37],"where":[38],"annotations":[39],"are":[40],"costly":[42],"time-intensive,":[44],"especially":[45],"in":[46,163],"medical":[47],"imaging.":[48],"Region-level":[49],"been":[52],"shown":[53],"to":[54],"be":[55],"efficient":[57],"than":[58],"image-level":[59],"these":[62,101,158],"tasks.":[63],"However,":[64],"existing":[65],"methods":[66,148],"representative":[68],"region":[70,80],"selection":[71],"suffer":[72],"from":[73,118],"high":[74],"computational":[75],"memory":[77],"costs,":[78],"irrelevant":[79],"choices,":[81],"heavy":[83],"reliance":[84],"uncertainty":[86],"sampling.":[87],"We":[88],"propose":[89],"decomposition":[90],"sampling":[91,97,116,127,151],"(DECOMP),":[92],"a":[93],"new":[94],"active":[95],"strategy":[98],"that":[99,130],"addresses":[100],"limitations.":[102],"It":[103],"enhances":[104],"diversity":[106],"decomposing":[108],"into":[110],"class-specific":[111],"components":[112],"using":[113],"pseudo-labels":[114],"regions":[117,153],"each":[119],"class.":[120],"Class-wise":[121],"predictive":[122],"confidence":[123],"further":[124],"guides":[125],"process,":[128],"ensuring":[129],"difficult":[131],"classes":[132],"receive":[133],"additional":[134],"annotations.":[135],"Across":[136],"ROI":[137],"classification,":[138],"2-D":[139],"segmentation,":[140,143],"3-D":[142],"DECOMP":[144],"consistently":[145],"surpasses":[146],"baseline":[147],"better":[150],"minority-class":[152],"boosting":[155],"performance":[156],"classes.":[160],"Code":[161],"is":[162],"https://github.com/JingnaQiu/DECOMP.git.":[164]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-05-06T00:00:00"}
