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• W2897558462 abstract "In this paper we present DCFE, a real-time facial landmark regression method based on a coarse-to-fine Ensemble of Regression Trees (ERT). We use a simple Convolutional Neural Network (CNN) to generate probability maps of landmarks location. These are further refined with the ERT regressor, which is initialized by fitting a 3D face model to the landmark maps. The coarse-to-fine structure of the ERT lets us address the combinatorial explosion of parts deformation. With the 3D model we also tackle other key problems such as robust regressor initialization, self occlusions, and simultaneous frontal and profile face analysis. In the experiments DCFE achieves the best reported result in AFLW, COFW, and 300 W private and common public data sets." @default.
• W2897558462 created "2018-10-26" @default.
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• W2897558462 date "2018-01-01" @default.
• W2897558462 modified "2023-10-14" @default.
• W2897558462 title "A Deeply-Initialized Coarse-to-fine Ensemble of Regression Trees for Face Alignment" @default.
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• W2897558462 doi "https://doi.org/10.1007/978-3-030-01264-9_36" @default.
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