Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model

ECCV 2018 Baris GecerBinod BhattaraiJosef KittlerTae-Kyun Kim

We propose a novel end-to-end semi-supervised adversarial framework to generate photorealistic face images of new identities with wide ranges of expressions, poses, and illuminations conditioned by a 3D morphable model. Previous adversarial style-transfer methods either supervise their networks with large volume of paired data or use unpaired data with a highly under-constrained two-way generative framework in an unsupervised fashion... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Face Verification IJB-A VGG + GANFaces TAR @ FAR=0.01 53.507% # 16
TAR @ FAR=0.001 18.768 # 3
Face Verification Labeled Faces in the Wild VGG + GANFaces Accuracy 94.9% # 19