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• W2956308084 abstract "Face alignment consists in aligning a shape model on a face in an image. It is an active domain in computer vision as it is a preprocessing for applications like facial expression recognition, face recognition and tracking, face animation, etc. Current state-of-the-art methods already perform well on easy datasets, i.e. those that present moderate variations in head pose, expression, illumination or partial occlusions, but may not be robust to in-the-wild data. In this paper, we address this problem by using an ensemble of deep regressors instead of a single large regressor. Furthermore, instead of averaging the outputs of each regressor, we propose an adaptive weighting scheme that uses a tree-structured gate. Experiments on several challenging face datasets demonstrate that our approach outperforms the state-of-the-art methods." @default.
• W2956308084 created "2019-07-23" @default.
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• W2956308084 date "2019-07-07" @default.
• W2956308084 modified "2023-09-24" @default.
• W2956308084 title "Tree-gated Deep Regressor Ensemble For Face Alignment In The Wild" @default.
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• W2956308084 hasPublicationYear "2019" @default.
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