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We propose a novel supervised initialization scheme for cascaded face alignment by searching nearest neighbors based on global image descriptors. Unlike existing schemes which resort to additional large training data sets for learning features, our method does not require additional training steps; thus making our method low computational. Moreover, we found that it is sufficient to use a simple low-dimensional...
Recently the use of image attributes as image descriptors has drawn great attention. This is because the resulting descriptors extracted using these attributes are human understandable as well as machine readable. Although the image attributes are generally semantically meaningful, they may not be discriminative. As such, prior works often consider a discriminative learning approach that could discover...
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