{"id":"https://openalex.org/W3009685396","doi":null,"title":"SketchTransfer: A New Dataset for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks","display_name":"SketchTransfer: A New Dataset for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3009685396","mag":"3009685396"},"language":"en","primary_location":{"id":"mag:3009685396","doi":null,"is_oa":false,"landing_page_url":"https://openaccess.thecvf.com/content_WACV_2020/papers/Lamb_SketchTransfer_A_New_Dataset_for_Exploring_Detail-Invariance_and_the_Abstractions_WACV_2020_paper.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"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/A5030891292","display_name":"Alex Lamb","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alex Lamb","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049332971","display_name":"Sherjil Ozair","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sherjil Ozair","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Vikas Verma","orcid":"https://orcid.org/0000-0002-8588-3433","observed_orcids":["https://orcid.org/0000-0002-8588-3433"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vikas Verma","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-8588-3433","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101406444","display_name":"David Ha","orcid":"https://orcid.org/0000-0001-9857-5950","observed_orcids":["https://orcid.org/0000-0001-9857-5950"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David Ha","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-9857-5950","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2533,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.56063986,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"963","last_page":"972"},"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":0.9994999766349792,"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":0.9994999766349792,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.00019999999494757503,"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/T10036","display_name":"Advanced Neural Network Applications","score":9.999999747378752e-05,"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/domain-adaptation","display_name":"domain adaptation","score":0.652999997138977},{"id":"https://openalex.org/keywords/datasets","display_name":"datasets","score":0.3190000057220459},{"id":"https://openalex.org/keywords/generalization","display_name":"generalization","score":0.44999998807907104},{"id":"https://openalex.org/keywords/domain-transfer","display_name":"domain transfer","score":0.5180000066757202},{"id":"https://openalex.org/keywords/visual-detail","display_name":"visual detail","score":0.3059999942779541},{"id":"https://openalex.org/keywords/3d-rendering","display_name":"3D rendering","score":0.550000011920929}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7216265201568604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5879853963851929},{"id":"https://openalex.org/C43803900","wikidata":"https://www.wikidata.org/wiki/Q170412","display_name":"Melody","level":3,"score":0.5359668731689453},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.4897201359272003},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4845098853111267},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4825286567211151},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47216910123825073},{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.4703904390335083},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4567199945449829},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.4464605450630188},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4330081343650818},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.42618003487586975},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35549384355545044},{"id":"https://openalex.org/C558565934","wikidata":"https://www.wikidata.org/wiki/Q2743","display_name":"Musical","level":2,"score":0.21939480304718018},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11775597929954529},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3009685396","doi":null,"is_oa":false,"landing_page_url":"https://openaccess.thecvf.com/content_WACV_2020/papers/Lamb_SketchTransfer_A_New_Dataset_for_Exploring_Detail-Invariance_and_the_Abstractions_WACV_2020_paper.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1837544984","https://openalex.org/W1924619199","https://openalex.org/W1997876580","https://openalex.org/W2466618734","https://openalex.org/W2606712314","https://openalex.org/W2767657961","https://openalex.org/W2786559811","https://openalex.org/W2788590143","https://openalex.org/W2795456585","https://openalex.org/W2890208753","https://openalex.org/W2902986194","https://openalex.org/W2909190397","https://openalex.org/W2910992787","https://openalex.org/W2921087533","https://openalex.org/W2921320475","https://openalex.org/W2921861056","https://openalex.org/W2936017220","https://openalex.org/W2940550985","https://openalex.org/W2943865428","https://openalex.org/W2944141891","https://openalex.org/W2948467580","https://openalex.org/W2952610664","https://openalex.org/W2962793481","https://openalex.org/W2963207607","https://openalex.org/W2963399829","https://openalex.org/W2963435192","https://openalex.org/W2964153729","https://openalex.org/W2964159205","https://openalex.org/W2976016473","https://openalex.org/W2976023236","https://openalex.org/W3004377989","https://openalex.org/W3006025420","https://openalex.org/W3034175346"],"related_works":["https://openalex.org/W3025009576","https://openalex.org/W3090508603","https://openalex.org/W2978165524","https://openalex.org/W7098253233","https://openalex.org/W2619569710","https://openalex.org/W3012305616","https://openalex.org/W2811385587","https://openalex.org/W2255259862","https://openalex.org/W3202034227","https://openalex.org/W3158944779"],"abstract_inverted_index":{"Deep":[0],"networks":[1],"have":[2,35],"achieved":[3],"excellent":[4],"results":[5],"in":[6,151],"perceptual":[7],"tasks,":[8],"yet":[9,78],"their":[10,32],"ability":[11,33],"to":[12,14,34,50,63,82,110,130,144,172],"generalize":[13],"variations":[15],"not":[16],"seen":[17],"during":[18],"training":[19],"has":[20,260],"come":[21],"under":[22],"increasing":[23],"scrutiny.":[24],"In":[26],"this":[27,146,199,251],"work":[28],"we":[29,189],"focus":[30],"on":[31,209,220,244],"invariance":[36],"towards":[37],"the":[38,120,125,138,157,174,221,236],"presence":[39],"or":[40],"absence":[41],"of":[42,140,159,235,239],"details.":[43],"For":[45],"example,":[46,69],"humans":[47,106],"are":[48,54,80,90,107],"able":[49,81,109],"watch":[51],"cartoons,":[52],"which":[53,205,224],"missing":[55,91],"many":[56],"visual":[57,104],"details,":[58],"without":[59],"being":[60],"explicitly":[61],"trained":[62,242],"do":[64,145],"so.":[65],"As":[67],"another":[68],"3D":[70],"rendering":[71],"software":[72],"is":[73,132,225,253],"a":[74,94,148,165,182,240],"relatively":[75],"recent":[76],"development,":[77],"people":[79],"understand":[83],"such":[84],"rendered":[85],"scenes":[86],"even":[87,123],"though":[88],"they":[89],"details":[92],"(consider":[93],"film":[95],"like":[96],"Toy":[97],"Story).":[98],"This":[100,248],"capability":[101],"goes":[102],"beyond":[103],"data:":[105],"easily":[108],"recognize":[111],"isolated":[112],"melodies":[113],"from":[114,133],"musical":[115],"pieces":[116],"when":[117],"heard":[118],"for":[119,185,263],"first":[121],"time,":[122],"if":[124],"only":[126,216],"piece":[127],"they've":[128],"listened":[129],"previously":[131],"an":[134],"orchestra.":[135],"Thus":[137],"failure":[139],"machine":[141],"learning":[142],"algorithms":[143,195],"indicates":[147,249],"significant":[149],"gap":[150],"generalization":[152],"between":[153],"human":[154],"abilities":[155,158],"and":[156,188],"deep":[160],"networks.":[161],"We":[163,180],"propose":[164],"dataset":[166],"that":[167,191,250],"will":[168],"make":[169],"it":[170],"easier":[171],"study":[173],"detail-invariance":[176],"problem":[177],"concretely.":[178],"produce":[181],"concrete":[183],"task":[184,252],"this:":[186],"SketchTransfer,":[187],"show":[190],"state-of-the-art":[192,203],"domain":[193],"transfer":[194,215],"still":[196],"struggle":[197],"with":[198,255],"task.":[200],"The":[202],"technique":[204],"achieves":[206,217],"over":[207],"95%":[208],"MNIST":[210],"\\xrightarrow":[211],"SVHN":[214],"59%":[218],"accuracy":[219,238],"SketchTransfer":[222],"task,":[223],"much":[226],"better":[227],"than":[228],"random":[229],"(11%":[230],"accuracy)":[231],"but":[232,259],"falls":[233],"short":[234],"87%":[237],"classifier":[241],"directly":[243],"labeled":[245],"sketches.":[246],"approachable":[254],"today's":[256],"best":[257],"methods":[258],"substantial":[261],"room":[262],"improvement.":[264]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2020-03-13T00:00:00"}