Deep Recurrent Regression for Facial Landmark Detection

We propose a novel end-to-end deep architecture for face landmark detection, based on a deep convolutional and deconvolutional network followed by carefully designed recurrent network structures. The pipeline of this architecture consists of three parts. Through the first part, we encode an input fa...

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Veröffentlicht in:	IEEE transactions on circuits and systems for video technology 2018-05, Vol.28 (5), p.1144-1157
Hauptverfasser:	Lai, Hanjiang, Xiao, Shengtao, Pan, Yan, Cui, Zhen, Feng, Jiashi, Xu, Chunyan, Yin, Jian, Yan, Shuicheng
Format:	Artikel
Sprache:	eng
Schlagworte:	Architecture Cascaded regression Computer architecture Face Face recognition facial landmark detection Feature extraction Feature maps Image resolution Landmarks Pipelines recurrent regression Shape shape-indexed features Visualization
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