Fashion Tech x Machine Learning/twm_fashion_ml

Transcript

1. Fashion Techͷ͋Μͪΐ͜
   -ػցֶशฤ-
   2016/4/16
   TokyoWebMining #53
   @tn1031
   

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2. Agenda
   1. Fashion x Technologyͷࣄྫ঺հ
   2. Fashion෼໺ͷݚڀࣄྫ
   3. ·ͱΊ
   2
   

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3. ࣗݾ঺հ
   ▸ தଜ ୓ຏ / @tn1031
   ▸ σʔλαΠΤϯςΟετ
   ▸ SIer(2೥൒) -> VASILY
   ▸ ػցֶशΛઐ߈
   ▸ ϊϯύϥϝτϦοΫϕΠζ
   ▸ ม෼ϕΠζ
   ▸ ϊϯύϥຊָ͕͠Έ
   ▸ TokyoWebMiningͷొஃ͸2ճ໨
   ▸ લճ͸ɺը૾ೝࣝʹ͍ͭͯൃද
   3
   @tn1031
   ਓ޻஌ೳ͸ɹɹɹɹɹ
   झຯͰᅂΉఔ౓
   

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4. VASILYͱiQONʹ͍ͭͯ
   

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5. VASILYͱiQONʹ͍ͭͯ
   ϑΝογϣϯΞϓϦʮiQONʯΛӡӦ͍ͯ͠·͢
   5
   

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6. VASILYͱiQONʹ͍ͭͯ
   Ϣʔβ͕ϑΝογϣϯΞΠςϜ
   Λ૊Έ߹ΘͤͯίʔσΛ࡞ΕΔ
   6
   

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7. VASILYͱiQONʹ͍ͭͯ
   ؾʹೖͬͨΞΠςϜ͸ͦͷ৔ͰECαΠτʹඈΜͰ͓ങ͍෺Ͱ͖Δ
   7
   ఏܞECαΠτ
   

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8. VASILYͱiQONʹ͍ͭͯ
   ೔ຊதͷECαΠτͷ঎඼৘ใΛΫϩʔϦϯά
   8
   

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9. VASILYͱiQONʹ͍ͭͯ
   iQON͕ѻ͏σʔλͷྫɿίʔσΟωʔτ
   9
   ίʔσ
   ‣ ࢖ΘΕͨΞΠςϜ
   ‣ ΞΠςϜͷϒϥϯυ
   ‣ ϨΠΞ΢τ
   ‣ λΠτϧ
   ‣ ίϝϯτ
   ‣ λά
   ‣ ɾɾɾ
   

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10. Fashion x Technologyͷࣄྫ঺հ
    

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11. Fashion x Technologyʁ
    ‣ ϑΝογϣϯۀք͸ɺ
    ‣ Ϗδωεͷن໛͕େ͖͍
    ‣ ੜ׆ʹ͔ܽͤͳ͍࢈ۀ
    ‣ IT͕ਁಁ͍ͯ͠ͳ͍
    11
    ϑΝογϣϯۀքʹɹɹɹɹɹ
    ITͷ೾͕དྷͯΔΒ͍͠
    

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12. Fashioning Data: A 2015 Update
    Data Innovations from the Fashion Industry
    12
    http://www.oreilly.com/data/free/fashioning-data.csp
    Έ͍ͨͳ͜ͱ͕ॻ͍ͯ͋Δຊ
    

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13. Fashion x Technologyͷࣄྫ
    ςΫϊϩδʔΛ׆͔ͨ͠αʔϏε͕ଟ਺ଘࡏ͢Δ
    13
    WHERETOGET
    ‣ http://wheretoget.it/
    Styloko
    ‣ https://www.styloko.com/
    deepomatic
    ‣ https://www.deepomatic.com/
    

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14. ࣄྫ1:WHERETOGE
    ‣ ϑΝογϣϯΞΠςϜͷը૾Λೖྗ͢ΔͱɺͦͷΞΠςϜ͕Ͳ͜Ͱख
    ʹೖΔͷ͔ڭ͑ͯ͘ΕΔαʔϏε
    ‣ ػց͕ݕࡧ͢ΔͷͰ͸ͳ͘ɺ஌͍ͬͯΔਓ͕ڭ͑ͯ͘ΕΔ
    14
    

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15. ࣄྫ2:Styloko
    ‣ ը૾Λೖྗ͢Δͱɺ৭΍ฑ͕Α͘ࣅͨΞΠςϜΛ୳ͯ͘͠ΕΔ
    ‣ ೖྗ͸(ͨͿΜ)෰Ͱͳͯ͘΋ྑ͍
    15
    

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16. ࣄྫ3:deepomatic
    ‣ ը૾͔ΒϑΝογϣϯ
    ΞΠςϜΛݕग़͠ɺը
    ૾ݕࡧͰಉ͡ΞΠςϜ
    Λฦ͢
    16
    

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17. Fashion x Technologyͷࣄྫ
    ‣ ը૾Λѻ͏αʔϏε͕ଟ͍
    ‣ ෰Λങ͏্Ͱ͔ܽͤͳ͍ཁૉ
    ‣ ݕࡧ΍ύʔιφϥΠζͷधཁ͕͋Δ
    ‣ େྔͷΞΠςϜ͔Β໨తͷΞΠςϜΛ୳͢
    ‣ ݸਓͷझ޲Λ൓өͨ͠ϥϯΩϯά
    17
    ϑΝογϣϯͱػցֶशͷ
    ਌࿨ੑ͸େ͖͍
    

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18. Fashion෼໺ͷݚڀࣄྫ
    

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19. FashionΛର৅ʹͨ͠ݚڀͰѻΘΕΔ໰୊
    19
    ը૾ܥͷख๏͸ϑΝογϣϯσʔλͱͷ਌࿨ੑ͕ߴ͍ɻҎԼͷ3߲໨͕ओྲྀͳҹ৅ɻ
    ΞΠςϜݕग़
    ύʔε ྖҬ෼ׂ
    
    ϑΝογϣϯ
    ΞΠςϜݕࡧ
    Ϩίϝϯυ
    ςʔϚ λεΫ ϑΝογϣϯྖҬ΁ͷద༻
    ը૾͔ΒΞΠςϜʹ֘౰͢ΔՕॴΛಛఆ͠ɺ
    ύʔε΍ΧςΰϦͷ൑ผΛߦ͏
    ѻ͏ը૾͕ݶఆ͞ΕΔҝɺ
    ࣄલ஌ࣝΛ׆༻Ͱ͖Δ
    ΫΤϦʹҰகɾྨࣅ͢Δ
    ΞΠςϜΛఏࣔ͢Δ
    ΤοδΛ༻͍ͨΞΠςϜͷ۠ผ͕ࠔ೉ͳҝɺ
    ৭΍ฑ΍ૉࡐͷ৘ใΛ൓өͰ͖ΔϞσϧ͕
    ඞཁ
    ߦಈσʔλ΍ΞΠςϜؒྨࣅ౓Λར༻ͯ͠ɺ
    Ϣʔβ΁ͷΞΠςϜఏࣔΛ࠷దԽ͢Δ
    ߦಈσʔλͷଞʹΞΠςϜͷը૾ಛ௃ྔ΍
    ྲྀߦΛϞσϧʹ૊ΈࠐΉ͜ͱ͕Ͱ͖Δ
    

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20. ΞΠςϜݕग़
    ‣ http://arxiv.org/abs/1411.5319
    ‣ http://arxiv.org/abs/1603.07063
    ‣ http://vision.is.tohoku.ac.jp/~kyamagu/papers/yamaguchi_cvpr2012.pdf
    20
    ը૾͔ΒΞΠςϜʹ֘౰͢ΔྖҬɾۣܗΛ੾Γग़͠ɺΧςΰϦ൑ผΛߦ͏ɻ
    ΞΠςϜ͕ݱΕΔ࠲ඪʹ͸نଇੑ͕͋Γɺ͜ͷੑ࣭ΛͲͷ༷ʹֶशʹར༻͢Δ͔͕ϙΠϯτɻ
    

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21. Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and
    Pose-dependent Priors (WACV 2016)
    ‣ ϑΝογϣϯΞΠςϜͷݕग़
    ‣ ண͍ͯΔ΋ͷ͚ͩͰͳ͘ɺ਎ʹ෇͚Δ΋ͷ΋ର৅ɹɹɹɹɹɹɹɹɹ
    (hat, glasses, bag, pants, shoes and so on.)
    ‣ ֶशʹDeep Convolutional Neural NetworkΛར༻
    ‣ ֤ΞΠςϜ͕ग़ݱ͠΍͍͢ҐஔΛࣄલ஌ࣝͱֶͯ͠शʹ׆༻͢Δ࢓૊Έ
    ΛఏҊ
    21
    ֓ཁ
    Fashion Apparel Detection: The Role of Deep
    Convolutional Neural Network and Pose-dependent Priors
    http://arxiv.org/abs/1411.5319
    

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22. Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and
    Pose-dependent Priors (WACV 2016)
    22
    Contribution
    ‣ domain-specific priorsͳࣄલ৘ใΛ׆༻ֶͨ͠शํ๏
    ΛఏҊͨ͠
    ‣ ϋϯυόοά͸खट΍खͷۙ͘ʹ͋Γɺۺ͸଍ͷۙ͘ʹग़ݱ͠
    қ͍
    ‣ ΞΠςϜͷେ͖͞͸͍ࣸͬͯΔਓͷେ͖͞ʹൺྫ͢Δ
    ‣ ϙʔζݕग़ΛߦͬͯΞΠςϜͷݕग़ਫ਼౓ΛߴΊͨ
    ‣ ΞΠςϜީิྖҬͷ࠲ඪͱϙʔζݕग़ͷग़ྗΛjoint͍ͤͯ͞Δ
    

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23. Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and
    Pose-dependent Priors (WACV 2016)
    23
    Overview of the proposed algorithm
    ‣ ΞΠςϜީิྖҬ͔Βͷಛ௃நग़͸CNNͰߦ͏
    ‣ ͦΕͧΕͷΫϥεͷग़ݱ֬཰Λ1-vs-rest SVMsͰݟੵ΋Δ
    ‣ ϙʔζਪఆʹجͮ͘Ґஔ৘ใʹΑͬͯ֬཰Λิਖ਼͢Δ
    ‣ Non-Maximum suppressionͰ੔͑ͯ࠷ऴతͳग़ྗͱ͢Δ
    

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24. Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and
    Pose-dependent Priors (WACV 2016)
    24
    Model
    Object Proposal
    ‣ ը૾͔ΒΞΠςϜྖҬͷީิΛऔಘ͢Δ
    ‣ ͦΕͧΕͷީิྖҬʹ͍ͭͯΞΠςϜͷ༗ແΛ൑ผ
    ثͰॲཧͯ͠false positiveΛݮΒ͢
    0CKFDU1SPQPTBM
    *NBHF'FBUVSF&YUSBDUJPO
    47.USBJOJOH
    1SPCBCJMJTUJDGPSNVMBUJPO
    "QQFBSBODFCBTFE1PTUFSJPS
    (FPNFUSJD1SJPST
    Image Feature Extraction
    ‣ ֶशࡁΈCaffeNetΛ༻͍Δ
    ‣ ग़ྗ૚ͷखલͷग़ྗ4096࣍ݩͷϕΫτϧΛಛ௃ྔͱ
    ͢Δ
    

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25. Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and
    Pose-dependent Priors (WACV 2016)
    25
    Model
    Appearance-based Posterior
    ‣ SVMͷύϥϝʔλΛར༻ͯ͠posteriorΛܭࢉ͢Δ
    ‣ ɹ
    ‣ λ͕൑ผਫ਼౓ʹޮ͍ͯ͘ΔͷͰɺ࠷ऴతͳ݁Ռʹجͮ
    ͖λΛνϡʔχϯά͢Δ
    0CKFDU1SPQPTBM
    *NBHF'FBUVSF&YUSBDUJPO
    47.USBJOJOH
    1SPCBCJMJTUJDGPSNVMBUJPO
    "QQFBSBODFCBTFE1PTUFSJPS
    (FPNFUSJD1SJPST
    SVM training
    ‣ ΞΠςϜͷΫϥε(bag,hat,...)ͦΕͧΕʹ͍ͭͯઢܗ
    SVMͰ2஋൑ผΛߦ͏
    

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26. Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and
    Pose-dependent Priors (WACV 2016)
    26
    Model
    0CKFDU1SPQPTBM
    *NBHF'FBUVSF&YUSBDUJPO
    47.USBJOJOH
    1SPCBCJMJTUJDGPSNVMBUJPO
    "QQFBSBODFCBTFE1PTUFSJPS
    (FPNFUSJD1SJPST
    Geometric Priors
    ‣ Ґஔ৘ใʹؔ͢ΔpriorΛ2छྨఆٛ͢Δ
    ‣ ۣܗͷप௕ʹ͍ͭͯɺ
    ‣ ۣܗͷΞεϖΫτൺʹ͍ͭͯɺ
    ‣ ۣܗͷத৺࠲ඪʹ͍ͭͯɺ
    Probabilistic formulation
    ‣ Appearance-based PosteriorͱGeometric Priors͔
    ΒPosteriorΛܭࢉ͢Δ
    

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27. Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and
    Pose-dependent Priors (WACV 2016)
    27
    Result
    

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28. ݕࡧ
    ‣ http://cseweb.ucsd.edu/~chunbinlin/papers/www16demo.pdf
    ‣ http://arxiv.org/pdf/1505.07922.pdf
    ‣ http://www.iis.sinica.edu.tw/papers/song/18378-F.pdf
    28
    طଘͷΞϧΰϦζϜΛϑΝογϣϯʹಛԽͤ͞ΔͨΊɺฑ΍ૉࡐͳͲͷ෇Ճ৘ใΛ༻͍Δɻ
    ΞΠςϜؒͷؔ܎Λฏ໘ʹϚοϐϯάͯ͠ΈΔͱָ͍͠ɻ
    

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29. Fashionista: A Fashion-aware Graphical System for Exploring Visually Similar Items
    (WWW 2016)
    ‣ ϑΝογϣϯΞΠςϜͷݕࡧγεςϜ
    ‣ ࢹ֮తʹྨࣅ͍ͯ͠ΔΞΠςϜͷݕࡧγεςϜΛ։ൃͨ͠
    ‣ graphical interfaceʹͩ͜ΘΓ͕͋Δ
    ‣ ྲྀߦΓΛ౿·্͑ͨͰࣅ͍ͯΔΞΠςϜΛఏࣔ͢Δ
    ‣ ֶशʹ༻͍Δ৘ใ
    ‣ ը૾ಛ௃ྔ
    ‣ AmazonͷߪങσʔλͱλΠϜελϯϓ
    29
    ֓ཁ
    Fashionista: A Fashion-aware Graphical System for
    Exploring Visually Similar Items
    http://cseweb.ucsd.edu/~chunbinlin/papers/www16demo.pdf
    

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30. Fashionista: A Fashion-aware Graphical System for Exploring Visually Similar
    Items(WWW 2016)
    30
    Contribution
    ‣ ࢹ֮తʹྨࣅ͍ͯ͠ΔΞΠςϜΛ୳ͤΔgraphical
    interface ”Fashionista”Λ։ൃͨ͠
    ‣ ࢹ֮తͳ৘ใ(ը૾ಛ௃ྔ)Λྨࣅ౓ܭࢉʹར༻͢Δ
    ‣ ”Fashionista”͸τϨϯυΛՄࢹԽͯ͠ࠓྲྀߦ͍ͬͯΔΞΠςϜΛ୳͠
    ΍͍ͯ͘͢͠Δ
    ‣ Amazon͔Β11೥ʹΘͨͬͯɺ0.6 million items, 1.8 million users,
    and 3.2 million user-item
    

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31. Fashionista: A Fashion-aware Graphical System for Exploring Visually Similar
    Items(WWW 2016)
    31
    A screenshot of Fashionista
    http://132.239.95.211:8080/demowww/index.jsp
    

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32. Fashionista: A Fashion-aware Graphical System for Exploring Visually Similar
    Items(WWW 2016)
    32
    Architecture of Fashionista
    

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33. Fashionista: A Fashion-aware Graphical System for Exploring Visually Similar
    Items(WWW 2016)
    33
    Fashion Learner
    5SBJOJOH%BUB
    ‣ Amazonͷߪങσʔλɹɹ
    (user, item, timestamp)
    ‣ pretrained CNN͔Βɹɹɹɹ
    ը૾ಛ௃ྔΛநग़
    'BTIJPO-FBSOFS ,OPXMFEHF
    ‣ ΞΠςϜಉ͕࢜ࣅ͍ͯΔʗࣅͯ
    ͍ͳ͍ͷ৘ใ
    ‣ tŖSNEͰѹॖͯ͠ฏ໘ʹɹ
    Ϛοϐϯά
    ‣ ΞΠςϜͷ͓͠ΌΕ౓ͷਪҠ
    ‣ Matrix Factorizationϕʔεͷख
    ๏ͰɺߦಈσʔλʹՃ͑ͯը૾
    ಛ௃ྔΛར༻͢Δ
    ‣ ҎԼͷ࣌ܥྻ৘ใΛѻ͏
    ‣ ΞΠςϜͷັྗʹ͍ͭͯͷ࣌
    ؒਪҠ
    ‣ ࢹ֮త৘ใʹର͢ΔϢʔβ
    ͷ൓ԠͷਪҠ
    ‣ Ϣʔβຖͷᅂ޷ͷมԽ
    

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34. Ϩίϝϯυ
    ‣ http://www.lv-nus.org/papers/2012/magic_closet-MM12.pdf
    ‣ http://labs.ebay.com/sites/default/files/14_fashionrecommender_kdd_ebayresearchlabs.pdf
    ‣ http://arxiv.org/abs/1506.04757
    34
    ߦಈσʔλ͚ͩͰͳ͘ɺΞΠςϜͷը૾ಛ௃ྔ΍ྲྀߦΛ൓өͤͨ͞ΞϧΰϦζϜ͕ఏҊ͞Ε͍ͯΔɻ
    Ϣʔβͷझ޲͚ͩͰͳ͘ɺΞΠςϜಉ࢜ͷ૬ੑΛߟྀͨ͠γεςϜ΋ଘࡏ͢Δɻ
    

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35. “Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012)
    ‣ occasionʹର͢ΔϨίϝϯσʔγϣϯ
    ‣ Wedding΍σʔτͱ͍ͬͨoccasionΛೖྗ͢Δͱɺࣗ਎
    ͷϑΥτΞϧόϜ΍ΦϯϥΠϯγϣοϓ͔Βద੾ͳ෰૷Λ
    ୳ͯ͠ఏҊͯ͘͠ΕΔ
    ‣ Magic Closet͕ղ͘໰୊͸2छྨ
    ‣ wear properly(ଐੑ)ɹɹɹɹɹɹɹɹɹɹɹɹɹɹɹɹ
    ʮόϯέοτʹ͸ύϯπεʔπΑΓυϨε͕ɹద͍ͯ͠Δʯ
    ‣ wear aesthetically(ඒ͠͞)ɹɹɹɹɹɹɹɹɹɹɹɹɹɹ
    ʮ੺͍Tγϟπʹ͸྘ΑΓനͷύϯπ͕ద͍ͯ͠Δʯ
    35
    ֓ཁ
    “Hi, Magic Closet, Tell Me What to Wear!"
    http://www.lv-nus.org/papers/2012/magic_closet-MM12.pdf
    

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36. “Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012)
    36
    Magic Closetͷ࢓૊Έ
    

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37. “Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012)
    37
    Magic Closetͷ࢓૊Έ
    TDFOBSJPɿPDDBTJPOΛࢦఆ
    ʮ*BNGPSBDPOGFSFODF QMFBTF
    SFDPNNFOETPNFUIJOHGSPNNZ
    QIPUPBMCVN ʯ
    TDFOBSJPɿPDDBTJPOͱ্൒਎ͷ෰Λࢦఆ
    ʮ*BNHPJOHPOBEBUF QMFBTFpOE
    TPNFUIJOHUPNBUDIXJUIUIJT5
    TIJSU ʯ
    

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38. “Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012)
    38
    Magic Closetͷ࢓૊Έ
    ز͔ͭͷ؍఺͔ΒϨίϝϯυΛߦ͏
    B
    "UUSJCVUFWT0DDBTJPO.PEFM
    ‣ ෰ͷଐੑͱPDDBTJPOͷ૬ੑ
    C
    "UUSJCVUFWT"UUSJCVUF.PEFM
    ‣ ෰ͷଐੑಉ࢜ͷ૬ੑ ্൒਎ͱԼ൒
    ਎
    
    D
    $MPUIJOH"UUSJCVUF&TUJNBUJPO
    ‣ ෰ͷଐੑͷਪఆ
    

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39. “Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012)
    39
    Magic Closetͷ࢓૊Έ
    ݁Ռͷग़ྗ
    PDDBTJPOΛࢦఆͨ͠৔߹ ྫɿDPOGFSFODF
    
    ‣ ద੾ͳ෰ ͷ૊Έ߹Θͤ
    ΛఏҊ
    PDDBTJPOͱ্൒਎ͷ෰Λࢦఆͨ͠৔߹ ྫɿ
    EBUF 5TIJSU
    
    ‣ ࢦఆͨ͠෰͓ΑͼPDDBTJPOͱ૬ੑͷྑ͍
    ෰ΛఏҊ
    

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40. “Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012)
    ‣ ҎԼͷ2ͭͷ໰୊ʹ࠷ॳʹऔΓ૊Μͩ
    ‣ ϑΥτΞϧόϜ͔Βoccasionʹదͨ͠෰૷Λ୳ͯ͠ਪન͢Δ
    ‣ ΫΤϦͷΞΠςϜ΍occasionʹ૬ੑͷྑ͍ΞΠςϜΛECαΠτ͔Β୳͢
    ‣ What-to-Wear (WoW)σʔληοτΛߏஙͨ͠
    ‣ 24,417ຕɺ౰࣌࠷େڃΒ͍͠
    ‣ occasionͱ෰ͷ૬ੑΛಉ࣌ʹֶश͢Δlatent SVMΛఏҊͨ͠
    40
    Contribution
    

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41. “Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012)
    ‣ ֶशσʔλ
    ‣
    ‣ :্൒਎/Լ൒਎ͷը૾ಛ௃ྔ ʗ :্൒਎ͷଐੑ(৭ͱ͔)ʗ
    :Լ൒਎ͷଐੑ ʗ :occasionΧςΰϦ
    41
    Model
    (
    x, au, al, o
    )
    ‣ Recommendation function
    x
    al
    au
    o
    

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42. “Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012)
    42
    Model
    'FBUVSFWT0DDBTJPO
    ‣ ը૾ಛ௃ྔͱoccasion
    ‣ ઢܗϞσϧ
    'FBUVSFWT"UUSJCVUF
    ‣ ը૾ಛ௃ྔͱ෰ͷଐੑ
    ‣ ઢܗϞσϧ
    "UUSJCVUFWT"UUSJCVUF
    ‣ ෰ͷଐੑͷ૊Έ߹Θͤ
    ͷ૬ੑ
    ‣ ্൒਎ͱԼ൒਎ͷϖΞ
    ʹ͍ͭͯܭࢉ͢Δ
    ‣ ্Լͷ෰ͷ૬ੑʹ͍ͭ
    ֶͯश͢Δ
    "UUSJCVUFWT0DDBTJPO
    ‣ ෰ͷଐੑͱoccasion
    ‣ ઢܗϞσϧ
    ‣ occasionʹదͨ͠෰૷
    Λֶश͢Δ
    

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43. “Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012)
    ‣ ӡ༻࣌
    ‣ occasionʹదͨ͠෰ͷϨίϝϯυ
    ‣ Լ൒਎givenͰ্൒਎ͷ෰ͷϨίϝϯυ
    ‣ ͜͜Ͱɺ
    43
    Model
    x
    ⇤
    = arg maxx
    2
    X
    t
    fw(x, o)
    x
    ⇤
    u = arg maxxu
    2
    X
    t
    u fw([xu; xl], o)
    fw(x, o) = max
    au,al
    w
    T
    (x, au, al, o)
    

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44. “Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012)
    44
    Result
    ΞΠςϜͷଐੑ
    ಉ࢜ͷ૬ੑ
    ଐੑͱoccasionͷ૬ੑ
    

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45. “Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012)
    45
    Result
    

    View Slide

46. ·ͱΊ
    

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47. ·ͱΊ
    ‣ Fashion x Technology͕੝Γ্͕͍ͬͯΔ
    ‣ TechnologyΛ׆༻ͨ͠αʔϏε͕ଟ਺ଘࡏ͢Δ
    ‣ ݚڀ։ൃ΋੝ΜʹߦΘΕ͍ͯΔ
    47
    

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48. ͝ਗ਼ௌ͋Γ͕ͱ͏͍͟͝·ͨ͠
    

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49. ࢀߟ
    ‣ http://cs229.stanford.edu/proj2009/McDanielsWorsley.pdf
    ‣ http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Simo-
    Serra_Neuroaesthetics_in_Fashion_2015_CVPR_paper.pdf
    ‣ http://labs.ebay.com/sites/default/files/13_stylefinder_cvpr_ebayresearchlabs.pdf
    ‣ http://vision.is.tohoku.ac.jp/~kyamagu/papers/yamaguchi_cvpr2012.pdf
    ‣ http://arxiv.org/abs/1411.5319
    ‣ http://labs.ebay.com/sites/default/files/14_fashionrecommender_kdd_ebayresearchlabs.pdf
    ‣ http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/
    Chen_Deep_Domain_Adaptation_2015_CVPR_paper.pdf
    ‣ http://arxiv.org/abs/1603.07063
    ‣ http://arxiv.org/abs/1506.04757
    ‣ http://cseweb.ucsd.edu/~chunbinlin/papers/www16demo.pdf
    ‣ http://arxiv.org/pdf/1505.07922.pdf
    ‣ http://www.iis.sinica.edu.tw/papers/song/18378-F.pdf
    ‣ http://arxiv.org/abs/1602.01585
    ‣ http://www.lv-nus.org/papers/2012/magic_closet-MM12.pdf
    ‣ http://arxiv.org/abs/1405.4013
    49
    

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