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The application of convolution neural network provides numerous opportunities to get performance of face recognition boosted. These opportunities require efficient deep face network structures as well as optimization methods for large datasets. However, existing deep face network structures mainly focus on stacking more convolutional layers while ignoring the importance of width. In this work, we...
Facial landmark detection is a challenging task with broad applications. Many approaches have been proposed with varying degrees of success. Regression based methods update the facial point positions iteratively. The mean shape or shapes sampled from training set is often used as the initialization, which sometimes may lead to a local minimum in update due to the offset of initial positions and target...
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