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arXiv · 1907.03248

Tree-gated Deep Regressor Ensemble For Face Alignment In The Wild

Estephe Arnaud·Arnaud Dapogny·Kevin Bailly
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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.

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Estephe Arnaud, Arnaud Dapogny, Kevin Bailly. 2019-07-07. Tree-gated Deep Regressor Ensemble For Face Alignment In The Wild. https://arxiv.org/abs/1907.03248

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