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3D face database is an important data platform for model training and algorithm design. As these works are mainly based on statistical learning, the coverage of training set has a great impact on algorithm performance. However it is a tedious process to obtain a 3D face sample. So the capacities of current 3D face databases are relatively insufficient. To solve this problem, we present a framework...