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We present variational generative adversarial networks, a general learning framework that combines a variational auto-encoder with a generative adversarial network, for synthesizing images in fine-grained categories, such as faces of a specific person or objects in a category. Our approach models an image as a composition of label and latent attributes in a probabilistic model. By varying the fine-grained...
We present a very efficient, highly accurate, “Explicit Shape Regression” approach for face alignment. Unlike previous regression-based approaches, we directly learn a vectorial regression function to infer the whole facial shape (a set of facial landmarks) from the image and explicitly minimize the alignment errors over the training data. The inherent shape constraint is naturally encoded into the...
According to analyzing the datum of the leakage currents from both perfect and faulty insulators that are at the state of various dirtiness, humidity, and temperature, and are applied non-sinusoidal voltages at different virtual values, three results are obtained. First, the bispectrum of the leakage current from contaminated insulator is mostly related to insulator; not to dirtiness. Bispectrum is...
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