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Storyboards for "Duke Goes To College"
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Breakdown sheet 1
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In modern face recognition, the conventional pipeline consists of four stages: detect ⇒ align ⇒ represent ⇒ clas- sify. We revisit both the alignment step and the representa- tion step by employing explicit 3D face modeling in order to apply a piecewise affine transformation, and derive a face representation from a nine-layer deep neural network. This deep network involves more than 120 million parameters using several locally connected layers without weight shar- ing, rather than the standard convolutional layers. Thus we trained it on the largest facial dataset to-date, an iden- tity labeled dataset of four million facial images belong- ing to more than 4,000 identities. The learned representa- tions coupling the accurate model-based alignment with the large facial database generalize remarkably well to faces in unconstrained environments, even with a simple classifier. Our method reaches an accuracy of 97.35% on the Labeled Faces in the Wild (LFW) dataset, reducing the error of the current state of the art by more than 27%, closely approach- ing human-level performance
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Duke goes to college shots
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