Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and Pose-dependent Priors (WACV 2016) ‣ ϑΝογϣϯΞΠςϜͷݕग़ ‣ ண͍ͯΔͷ͚ͩͰͳ͘ɺʹ͚Δͷରɹɹɹɹɹɹɹɹɹ (hat, glasses, bag, pants, shoes and so on.) ‣ ֶशʹDeep Convolutional Neural NetworkΛར༻ ‣ ֤ΞΠςϜ͕ग़ݱ͍͢͠ҐஔΛࣄલࣝͱֶͯ͠शʹ׆༻͢ΔΈ ΛఏҊ 21 ֓ཁ Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and Pose-dependent Priors http://arxiv.org/abs/1411.5319
Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and Pose-dependent Priors (WACV 2016) 23 Overview of the proposed algorithm ‣ ΞΠςϜީิྖҬ͔Βͷಛநग़CNNͰߦ͏ ‣ ͦΕͧΕͷΫϥεͷग़ݱ֬Λ1-vs-rest SVMsͰݟੵΔ ‣ ϙʔζਪఆʹجͮ͘ҐஔใʹΑͬͯ֬Λิਖ਼͢Δ ‣ Non-Maximum suppressionͰ͑ͯ࠷ऴతͳग़ྗͱ͢Δ
Fashionista: A Fashion-aware Graphical System for Exploring Visually Similar Items (WWW 2016) ‣ ϑΝογϣϯΞΠςϜͷݕࡧγεςϜ ‣ ࢹ֮తʹྨࣅ͍ͯ͠ΔΞΠςϜͷݕࡧγεςϜΛ։ൃͨ͠ ‣ graphical interfaceʹͩ͜ΘΓ͕͋Δ ‣ ྲྀߦΓΛ౿·্͑ͨͰࣅ͍ͯΔΞΠςϜΛఏࣔ͢Δ ‣ ֶशʹ༻͍Δใ ‣ ը૾ಛྔ ‣ AmazonͷߪങσʔλͱλΠϜελϯϓ 29 ֓ཁ Fashionista: A Fashion-aware Graphical System for Exploring Visually Similar Items http://cseweb.ucsd.edu/~chunbinlin/papers/www16demo.pdf
Fashionista: A Fashion-aware Graphical System for Exploring Visually Similar Items(WWW 2016) 30 Contribution ‣ ࢹ֮తʹྨࣅ͍ͯ͠ΔΞΠςϜΛ୳ͤΔgraphical interface ”Fashionista”Λ։ൃͨ͠ ‣ ࢹ֮తͳใ(ը૾ಛྔ)Λྨࣅܭࢉʹར༻͢Δ ‣ ”Fashionista”τϨϯυΛՄࢹԽͯ͠ࠓྲྀߦ͍ͬͯΔΞΠςϜΛ୳͠ ͍ͯ͘͢͠Δ ‣ Amazon͔Β11ʹΘͨͬͯɺ0.6 million items, 1.8 million users, and 3.2 million user-item
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
“Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012) 38 Magic ClosetͷΈ ز͔ͭͷ؍͔ΒϨίϝϯυΛߦ͏ B "UUSJCVUFWT0DDBTJPO.PEFM ‣ ͷଐੑͱPDDBTJPOͷ૬ੑ C "UUSJCVUFWT"UUSJCVUF.PEFM ‣ ͷଐੑಉ࢜ͷ૬ੑ ্ͱԼ
“Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012) ‣ ֶशσʔλ ‣ ‣ :্/Լͷը૾ಛྔ ʗ :্ͷଐੑ(৭ͱ͔)ʗ :Լͷଐੑ ʗ :occasionΧςΰϦ 41 Model ( x, au, al, o ) ‣ Recommendation function x al au o
“Hi, Magic Closet, Tell Me What toWear!”(ACM MM 2012) ‣ ӡ༻࣌ ‣ occasionʹదͨ͠ͷϨίϝϯυ ‣ ԼgivenͰ্ͷͷϨίϝϯυ ‣ ͜͜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)