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Expression and pose variations are major challenges for reliable face recognition (FR) in 2D. In this paper, we aim to endow state of the art face recognition SDKs with robustness to facial expression variations and pose changes by using an extended 3D Morphable Model (3DMM) which isolates identity variations from those due to facial expressions.(More)
The deployment of cameras for security control allows for video stream to be used as input for face recognition (FR). However, most state of the art FR SDKs are generally specifically tuned for dealing with frontal and neutral face images, whereas expression and pose variations, which typically occur in unconstrained settings, e.g., video images, are still(More)
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