{"id":"https://openalex.org/W7097728844","doi":null,"title":"K.: LSDA: Large scale detection through adaptation","display_name":"K.: LSDA: Large scale detection through adaptation","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W7097728844"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.767.2441","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.767.2441","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1407.5035.pdf","raw_type":"text"},"volume":null,"type":"preprint","indexed_in":[],"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/A5038068459","display_name":"Judy Hoffman","orcid":"https://orcid.org/0000-0003-1971-1606","observed_orcids":["https://orcid.org/0000-0003-1971-1606"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Judy Hoffman","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004083108","display_name":"Sergio Guadarrama","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sergio Guadarrama","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025289132","display_name":"Eric Tzeng","orcid":"https://orcid.org/0009-0008-9397-2429","observed_orcids":["https://orcid.org/0009-0008-9397-2429"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eric Tzeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039012309","display_name":"Jeff Donahue","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeff Donahue","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049246408","display_name":"Ross Girshick","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ross Girshick","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029105520","display_name":"Trevor Darrell","orcid":"https://orcid.org/0000-0001-5453-8533","observed_orcids":["https://orcid.org/0000-0001-5453-8533"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Trevor Darrell","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5075906727","display_name":"Kate Saenko","orcid":"https://orcid.org/0000-0002-7564-7218","observed_orcids":["https://orcid.org/0000-0002-7564-7218","https://orcid.org/0000-0002-5704-7614"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kate Saenko","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":true,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9702000021934509,"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":0.9702000021934509,"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":0.024800000712275505,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.0031999999191612005,"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/object-detection","display_name":"object detection","score":0.9129999876022339},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.6389999985694885},{"id":"https://openalex.org/keywords/image-classification","display_name":"image classification","score":0.41999998688697815},{"id":"https://openalex.org/keywords/bounding-box-annotation","display_name":"bounding box annotation","score":0.6079999804496765},{"id":"https://openalex.org/keywords/imagenet","display_name":"ImageNet","score":0.5400000214576721}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.751800000667572},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7265999913215637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.714900016784668},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.6625000238418579},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5784000158309937},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5242999792098999},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5012000203132629},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4934999942779541},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.47929999232292175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4742000102996826},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4255000054836273},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.41920000314712524},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4133000075817108},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.40119999647140503},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.38929998874664307},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.37619999051094055},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.3650999963283539},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31209999322891235},{"id":"https://openalex.org/C34872919","wikidata":"https://www.wikidata.org/wiki/Q7092302","display_name":"One-class classification","level":3,"score":0.29739999771118164},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2775999903678894},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.2736999988555908},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2694999873638153},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.767.2441","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.767.2441","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/1407.5035.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7098006858","https://openalex.org/W2188721014","https://openalex.org/W3118508671","https://openalex.org/W2990998780","https://openalex.org/W4221142320","https://openalex.org/W2963813458","https://openalex.org/W4412468250","https://openalex.org/W4312305279","https://openalex.org/W3027847410","https://openalex.org/W4312424618"],"abstract_inverted_index":{"A":[0],"major":[1],"challenge":[2,156],"in":[3,34,180],"scaling":[4],"object":[5,31],"detection":[6,56,79,155],"is":[7,59,76],"the":[8,55,101,104,127,133,152,158,181],"difficulty":[9],"of":[10,17,49,68,135,137,147,160],"obtaining":[11],"la-beled":[12],"images":[13],"for":[14,54,113,132],"large":[15,66],"numbers":[16],"categories.":[18],"Recently,":[19],"deep":[20],"convolutional":[21],"neural":[22],"networks":[23],"(CNN)":[24],"have":[25,145],"emerged":[26],"as":[27],"clear":[28],"winners":[29],"on":[30,151],"classification":[32,42,148,174],"bench-marks,":[33],"part":[35],"due":[36],"to":[37,64,77,111,129,167,172],"training":[38],"with":[39,84],"1.2M+":[40],"labeled":[41],"images.":[43],"Un-fortunately,":[44],"only":[45],"a":[46,93],"small":[47],"fraction":[48],"those":[50],"labels":[51],"are":[52,187],"available":[53,173,188],"task.":[57],"It":[58],"much":[60],"cheaper":[61],"and":[62,81,107,185],"easier":[63],"collect":[65,78],"quantities":[67],"image-level":[69],"la-bels":[70],"from":[71,176],"search":[72],"engines":[73],"than":[74],"it":[75,83],"data":[80,175],"label":[82],"pre-cise":[85],"bounding":[86,116,141],"boxes.":[87],"In":[88],"this":[89,109],"paper,":[90],"we":[91],"propose":[92],"Deep":[94],"Detection":[95],"Adaptation":[96],"(DDA)":[97],"algorithm":[98,164],"which":[99],"learns":[100],"difference":[102],"between":[103],"two":[105],"tasks":[106],"trans-fers":[108],"knowledge":[110],"classifiers":[112],"categories":[114,138],"without":[115],"box":[117,142],"annotated":[118],"data,":[119],"turning":[120],"them":[121],"into":[122],"detectors.":[123],"Our":[124],"method":[125],"has":[126],"potential":[128],"enable":[130],"detec-tion":[131],"tens":[134],"thousands":[136],"that":[139],"lack":[140],"annotations,":[143],"yet":[144],"plenty":[146],"data.":[149],"Evaluation":[150],"ImageNet":[153,182],"LSVRC-2013":[154],"demonstrates":[157],"efficacy":[159],"our":[161],"approach.":[162],"This":[163],"enables":[165],"us":[166],"produce":[168],"a>7.5K":[169],"detector":[170],"corresponding":[171],"all":[177],"leaf":[178],"nodes":[179],"tree.":[183],"Models":[184],"software":[186],"at":[189],"lsda.berkeleyvision.org.":[190],"1":[191]},"counts_by_year":[],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2025-10-27T00:00:00"}