Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network

CVPR 2017 Anh Tuan TranTal HassnerIacopo MasiGerard Medioni

The 3D shapes of faces are well known to be discriminative. Yet despite this, they are rarely used for face recognition and always under controlled viewing conditions... (read more)

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Results from the Paper


Ranked #4 on 3D Face Reconstruction on Florence (Average 3D Error metric)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
3D Face Reconstruction Florence 3DMM-CNN Average 3D Error 1.93 # 4
Face Verification Labeled Faces in the Wild 3DMM face shape parameters + CNN Accuracy 92.35% # 21
Face Verification YouTube Faces DB 3DMM face shape parameters + CNN Accuracy 88.80% # 12

Methods used in the Paper


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