DeepFace: Closing the Gap to Human-Level Performance in Face Verification

In modern face recognition, the conventional pipeline consists of four stages: detect => align => represent => classify. We revisit both the alignment step and the representation 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... (read more)

PDF Abstract Conference on Computer Vision and Pattern Recognition (CVPR) 2014 PDF Conference on Computer Vision and Pattern Recognition (CVPR) 2014 Abstract

Datasets


Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Face Verification Labeled Faces in the Wild DeepFace Accuracy 98.37% # 23
3D FACE MODELING LFW DeepFace 1-of-100 Accuracy 70 # 1

Methods used in the Paper


METHOD TYPE
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