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• W2465108587 abstract "Large-pose face alignment is a very challenging problem in computer vision, which is used as a prerequisite for many important vision tasks, e.g, face recognition and 3D face reconstruction. Recently, there have been a few attempts to solve this problem, but still more research is needed to achieve highly accurate results. In this paper, we propose a face alignment method for large-pose face images, by combining the powerful cascaded CNN regressor method and 3DMM. We formulate the face alignment as a 3DMM fitting problem, where the camera projection matrix and 3D shape parameters are estimated by a cascade of CNN-based regressors. The dense 3D shape allows us to design pose-invariant appearance features for effective CNN learning. Extensive experiments are conducted on the challenging databases (AFLW and AFW), with comparison to the state of the art." @default.
• W2465108587 created "2016-07-22" @default.
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• W2465108587 date "2016-06-01" @default.
• W2465108587 modified "2023-10-01" @default.
• W2465108587 title "Large-Pose Face Alignment via CNN-Based Dense 3D Model Fitting" @default.
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• W2465108587 doi "https://doi.org/10.1109/cvpr.2016.454" @default.
• W2465108587 hasPublicationYear "2016" @default.
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