{"id":"https://openalex.org/W2981488580","doi":"https://doi.org/10.1109/iccv.2019.00195","title":"Switchable Whitening for Deep Representation Learning","display_name":"Switchable Whitening for Deep Representation Learning","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2981488580","doi":"https://doi.org/10.1109/iccv.2019.00195","mag":"2981488580"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2019.00195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2019.00195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"article","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/A5052549072","display_name":"Xingang Pan","orcid":"https://orcid.org/0000-0002-5825-9467"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xingang Pan","raw_affiliation_strings":["CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040988693","display_name":"Xiaohang Zhan","orcid":"https://orcid.org/0000-0003-2136-7592"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohang Zhan","raw_affiliation_strings":["CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103125510","display_name":"Jianping Shi","orcid":"https://orcid.org/0000-0003-3257-8272"},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianping Shi","raw_affiliation_strings":["SenseTime Group Limited"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Group Limited","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110380387","display_name":"Xiaoou Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoou Tang","raw_affiliation_strings":["CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100752686","display_name":"Ping Luo","orcid":"https://orcid.org/0000-0002-6685-7950"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]},{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Ping Luo","raw_affiliation_strings":["CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong","The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5052549072"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":4.1845,"has_fulltext":false,"cited_by_count":164,"citation_normalized_percentile":{"value":0.95389803,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1863","last_page":"1871"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9991999864578247,"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/normalization","display_name":"Normalization (sociology)","score":0.8416513204574585},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7809696197509766},{"id":"https://openalex.org/keywords/standardization","display_name":"Standardization","score":0.7267236113548279},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6961556673049927},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5787769556045532},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.539444088935852},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5374963879585266},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5018115043640137},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48223528265953064},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.45419150590896606},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.438802570104599},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4157271981239319},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3848954439163208},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.31963467597961426},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.0748123824596405}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.8416513204574585},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7809696197509766},{"id":"https://openalex.org/C188087704","wikidata":"https://www.wikidata.org/wiki/Q369577","display_name":"Standardization","level":2,"score":0.7267236113548279},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6961556673049927},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5787769556045532},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.539444088935852},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5374963879585266},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5018115043640137},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48223528265953064},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.45419150590896606},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.438802570104599},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4157271981239319},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3848954439163208},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.31963467597961426},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0748123824596405},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccv.2019.00195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2019.00195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/CVF International Conference on Computer Vision (ICCV)","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":0.8399999737739563}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1861492603","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2212660284","https://openalex.org/W2331128040","https://openalex.org/W2340897893","https://openalex.org/W2412782625","https://openalex.org/W2487365028","https://openalex.org/W2507296351","https://openalex.org/W2558580397","https://openalex.org/W2560023338","https://openalex.org/W2563705555","https://openalex.org/W2572730214","https://openalex.org/W2588610957","https://openalex.org/W2603777577","https://openalex.org/W2617322972","https://openalex.org/W2617602381","https://openalex.org/W2737258237","https://openalex.org/W2786689170","https://openalex.org/W2789983685","https://openalex.org/W2803808038","https://openalex.org/W2807205843","https://openalex.org/W2811135961","https://openalex.org/W2884366600","https://openalex.org/W2895340641","https://openalex.org/W2901096562","https://openalex.org/W2949117887","https://openalex.org/W2949341804","https://openalex.org/W2962772087","https://openalex.org/W2963107255","https://openalex.org/W2963300719","https://openalex.org/W2963314703","https://openalex.org/W2963318290","https://openalex.org/W2963727650","https://openalex.org/W2963743626","https://openalex.org/W2963840672","https://openalex.org/W2963857170","https://openalex.org/W3118608800","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6639102338","https://openalex.org/W6640002369","https://openalex.org/W6688325169","https://openalex.org/W6696085341","https://openalex.org/W6702130928","https://openalex.org/W6722836162","https://openalex.org/W6724670942","https://openalex.org/W6730845260","https://openalex.org/W6733590821","https://openalex.org/W6737965738","https://openalex.org/W6738438352","https://openalex.org/W6748281876","https://openalex.org/W6749010802","https://openalex.org/W6749954789","https://openalex.org/W6751546485","https://openalex.org/W6752691321","https://openalex.org/W6753055032","https://openalex.org/W6754713557","https://openalex.org/W6756274528","https://openalex.org/W6780226713"],"related_works":["https://openalex.org/W2378767206","https://openalex.org/W1540871478","https://openalex.org/W328308450","https://openalex.org/W282641168","https://openalex.org/W2376963063","https://openalex.org/W2066396794","https://openalex.org/W2366734808","https://openalex.org/W2002476357","https://openalex.org/W2391444248","https://openalex.org/W2390716080"],"abstract_inverted_index":{"Normalization":[0],"methods":[1,47],"are":[2],"essential":[3],"components":[4],"in":[5,19,60,109],"convolutional":[6],"neural":[7],"networks":[8],"(CNNs).":[9],"They":[10],"either":[11],"standardize":[12],"or":[13,74],"whiten":[14],"data":[15],"using":[16],"statistics":[17,76],"estimated":[18],"predefined":[20],"sets":[21],"of":[22,90,99,124],"pixels.":[23],"Unlike":[24],"existing":[25],"works":[26],"that":[27,131],"design":[28],"normalization":[29],"techniques":[30],"for":[31,77,86,120],"specific":[32],"tasks,":[33],"we":[34,160],"propose":[35],"Switchable":[36],"Whitening":[37],"(SW),":[38],"which":[39],"provides":[40],"a":[41,87,117],"general":[42],"form":[43],"unifying":[44],"different":[45,78,100],"whitening":[46,73,125],"as":[48,50,116],"well":[49,84],"standardization":[51,75,127],"methods.":[52],"SW":[53,69,102,114,132],"learns":[54],"to":[55],"switch":[56],"among":[57],"these":[58],"operations":[59],"an":[61],"end-to-end":[62],"manner.":[63],"It":[64],"has":[65],"several":[66],"advantages.":[67],"First,":[68],"adaptively":[70],"selects":[71],"appropriate":[72],"tasks":[79,91],"(see":[80],"Fig.1),":[81],"making":[82],"it":[83],"suited":[85],"wide":[88],"range":[89],"without":[92,156],"manual":[93],"design.":[94],"Second,":[95],"by":[96],"integrating":[97],"benefits":[98],"normalizers,":[101],"shows":[103],"consistent":[104],"improvements":[105],"over":[106],"its":[107],"counterparts":[108],"various":[110],"challenging":[111],"benchmarks.":[112],"Third,":[113],"serves":[115],"useful":[118],"tool":[119],"understanding":[121],"the":[122,168],"characteristics":[123],"and":[126,149,158],"techniques.":[128],"We":[129],"show":[130],"outperforms":[133],"other":[134],"alternatives":[135],"on":[136,167],"image":[137,150],"classification":[138],"(CIFAR-10/100,":[139],"ImageNet),":[140],"semantic":[141],"segmentation":[142],"(ADE20K,":[143],"Cityscapes),":[144,148],"domain":[145],"adaptation":[146],"(GTA5,":[147],"style":[151],"transfer":[152],"(COCO).":[153],"For":[154],"example,":[155],"bells":[157],"whistles,":[159],"achieve":[161],"state-of-the-art":[162],"performance":[163],"with":[164],"45.33%":[165],"mIoU":[166],"ADE20K":[169],"dataset.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":33},{"year":2024,"cited_by_count":47},{"year":2023,"cited_by_count":32},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1}],"updated_date":"2026-05-09T13:55:54.758798","created_date":"2025-10-10T00:00:00"}