cvim saisentan-cvpr-deep face

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  • DeepFace: Closing the Gap to Human-Level Performance in Face Verication Yaniv Taigman* Ming Yang* MarcAurelio Ranzato* Lior Wolf** *:Facebook AI Research **:Tel Aviv University Tomoaki Teshima @tomoaki_teshima
  • Contributions DNN architecture Facial alignment based on 3D model Result LFW human performance YTF low error rate
  • Verification CV6 (@dandelion1124) Verification Object categorization Identification Detection Scene and context categorization DeepFace: Closing the Gap to Human- Level Performance in Face Verication
  • Modern face recognition detect align represent classify Constrained/Unconstrained
  • Face Alignment
  • Face Alignment in 2D () 6 Cropped area (2) (2)
  • Face Alignment in 3D () Second SVR 2D aligned image USF Human ID database Frontalization
  • DNN architecture Face feature SFC4030
  • Max pooling Convolution
  • L4L5L6
  • L7L8 DropoutL7
  • SFC Shonan Fujisawa Campus Super Famicom
  • SFC() Santos Futebol Clube, a Brazilian football club Scarborough F.C., a dissolved English football club Servette FC, a Swiss football club Sevilla FC, a Spanish football club SFC Opava, a Czech football club Shelbourne F.C., an Irish football club Sheffield F.C., an English football club Southampton F.C., an English football club Southport F.C., an English football club Spartans F.C. A Punes football club Sriwijaya F.C., an Indonesia football club Stamford F.C., an English football club Stenhousemuir F.C., a Scottish football club Stevenage F.C., an English football club Stranraer F.C., a Scottish football club Sydney FC, an Australian football club Syrianska FC, a Swedish football club
  • SFC() The proposed face representation is learned from a large collection of photos from Facebook, referred to as the Social Face Classification (SFC) dataset.
  • L7L8() DropoutL7
  • Normalization L2
  • Verification Metric Weighted 2 distance Simanse network
  • dataset SFC Social Face Classification LFW Labeled Faces in the Wild YTF Youtube Faces SFC 3% SFC expression LFWYTF
  • 5.2. Training on the SFC
  • 5.3. Results on the LFW dataset
  • 5.4. Results on the YTF dataset
  • 5.5 Computational efficiency SIMD Intel2.2GHz Feed forward network classification Total0.33s
  • Deep FaceDeep Learning Verification
  • _20101023_dandelion.pdf, @dandelion1124 /Super_Famicom_JPN.jpg mnetwork.pdf df