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Priming Deep Neural Networks with Synthetic Faces for Enhanced Performance., , , , , , , and . CoRR, (2018)Analyzing and Reducing the Damage of Dataset Bias to Face Recognition With Synthetic Data., , , , , and . CVPR Workshops, page 0. Computer Vision Foundation / IEEE, (2019)Training Deep Face Recognition Systems with Synthetic Data., , , , , and . CoRR, (2018)Gaussian Process Morphable Models., , , and . CoRR, (2016)Morphable Face Models - An Open Framework., , , , , , and . CoRR, (2017)Empirically Analyzing the Effect of Dataset Biases on Deep Face Recognition Systems., , , , , and . CVPR Workshops, page 2093-2102. IEEE Computer Society, (2018)Error-Controlled Model Approximation for Gaussian Process Morphable Models., , , , and . Journal of Mathematical Imaging and Vision, 61 (4): 443-457 (2019)Supervised learning for bone shape and cortical thickness estimation from CT images for finite element analysis., , , , and . Medical Image Analysis, (2019)Posterior shape models., , , and . Medical Image Analysis, 17 (8): 959-973 (2013)Empirically Analyzing the Effect of Dataset Biases on Deep Face Recognition Systems., , , , , and . CoRR, (2017)