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ID:40352888
大小:623.97 KB
页数:10页
时间:2019-07-31
《cvpr18-Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、TransferableJointAttribute-IdentityDeepLearningforUnsupervisedPersonRe-IdentificationJingyaWang1XiatianZhu2ShaogangGong1WeiLi1QueenMaryUniversityofLondon1VisionSemanticsLtd.2{jingya.wang,s.gong,w.li}@qmul.ac.ukeddy@visionsemantics.comAbstractinthereal-worldasthereareaquadraticnumberofcamerap
2、airs,butalsoimplausibleinmanycases,e.g.theremaynotMostexistingpersonre-identification(re-id)methodsre-existsufficienttrainingpeoplereappearingineverypairofquiresupervisedmodellearningfromaseparatelargesetcameraviews.Thisscalabilitylimitationseverelyreducesofpairwiselabelledtrainingdataforever
3、ysinglecameratheusabilityofexistingsupervisedre-idmethods.pair.Thissignificantlylimitstheirscalabilityandusabil-Onegenericsolutiontolargescalere-idinreal-worldityinreal-worldlargescaledeploymentswiththeneedfordeploymentisdesigningunsupervisedmodels.Whileafewperformingre-idacrossmanycameravie
4、ws.Toaddressunsupervisedmethodshavebeendeveloped[13,9,21,20,thisscalabilityproblem,wedevelopanoveldeeplearn-34,51,61],theytypicallyofferweakerre-idperformancesingmethodfortransferringthelabelledinformationofanwhencomparedtothesupervisedcounterparts.Thismakesexistingdatasettoanewunseen(unlab
5、elled)targetdo-themlessusefulinpractice.Onemainreasonisthatwith-mainforpersonre-idwithoutanysupervisedlearninginoutlabelleddataacrossviews,unsupervisedmethodslackthetargetdomain.Specifically,weintroduceanTransfer-thenecessaryknowledgeonhowvisualappearanceofiden-ableJointAttribute-IdentityDee
6、pLearning(TJ-AIDL)forticalobjectschangescross-viewsduetodifferentviewan-simultaneouslylearninganattribute-semanticandidentity-gles,backgroundandillumination.Anothersolutionistodiscriminativefeaturerepresentationspacetransferrabletoexploitsimultaneously(1)unlabelleddatafromatargetdo-anynew(u
7、nseen)targetdomainforre-idtaskswithoutthemainand(2)existinglabelleddatasetsfromsometrainingneedforcollectingnewlabelledtrainingdatafromthetar-sourcedomains.Specifically,theideaistolearnafeaturegetdomain(i.e.unsupervisedlearninginthetargetdo-representation
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