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Deep Structured Prediction for Facial Landmark Detection

2020-10-18NeurIPS 2019Code Available1· sign in to hype

Lisha Chen, Hui Su, Qiang Ji

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Abstract

Existing deep learning based facial landmark detection methods have achieved excellent performance. These methods, however, do not explicitly embed the structural dependencies among landmark points. They hence cannot preserve the geometric relationships between landmark points or generalize well to challenging conditions or unseen data. This paper proposes a method for deep structured facial landmark detection based on combining a deep Convolutional Network with a Conditional Random Field. We demonstrate its superior performance to existing state-of-the-art techniques in facial landmark detection, especially a better generalization ability on challenging datasets that include large pose and occlusion.

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DatasetModelMetricClaimedVerifiedStatus
300WCNN-CRF (Inter-ocular Norm)NME3.3Unverified

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