Tweaked residual convolutional network for face alignment
نویسندگان
چکیده
منابع مشابه
Improved Face Detection and Alignment using Cascade Deep Convolutional Network
Real-world face detection and alignment demand an advanced discriminative model to address challenges by pose, lighting and expression. Recent studies have utilized the relation between face detection and alignment to make models computationally efficiency, but they ignore the connection between each cascade CNNs. In this paper, we combine detection, calibration and alignment in each Cascade CN...
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Face recognition in real-world images mostly relies on three successive steps: face detection, alignment and identification. The second step of face alignment is crucial as the bounding boxes produced by robust face detection algorithms are still too imprecise for most face recognition techniques, i.e. they show slight variations in position, orientation and scale. We present a novel technique ...
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Face alignment is critical for face recognition, and the deep learning-based method shows promise for solving such issues, given that competitive results are achieved on benchmarks with additional benefits, such as dispensing with handcrafted features and initial shape. However, most existing deep learning-based approaches are complicated and quite time-consuming during training. We propose a c...
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Methods for unconstrained face alignment must satisfy two requirements: (a) they must not rely on accurate initialization/face detection and (b) they should perform equally well for the whole spectrum of facial pose. To the best of our knowledge, there are no methods meeting these requirements to satisfactory extent, and in this paper, we propose Convolutional Aggregation of Local Evidence (CAL...
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Article history: Received 27 April 2015 Received in revised form 8 June 2015 Accepted 8 June 2015 Available online 16 June 2015
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ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2017
ISSN: 1742-6588,1742-6596
DOI: 10.1088/1742-6596/887/1/012077