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We present a novel and effective approach for generating new clothing on a wearer through generative adversarial learning. Given an input image of a person and a sentence describing a different outfit, our model “redresses” the person as desired, while at the same time keeping the wearer and her/his pose unchanged. Generating new outfits with precise regions conforming to a language description while...
We present a practical approach to address the problem of unconstrained face alignment for a single image. In our unconstrained problem, we need to deal with large shape and appearance variations under extreme head poses and rich shape deformation. To equip cascaded regressors with the capability to handle global shape variation and irregular appearance-shape relation in the unconstrained scenario,...
In recent years, the Internet has emerged as an alternative information source on mental health problems. Yet, the profile of the typical Internet help seeker is to be determined. Based on data from a household survey of 2558 Beijing residents, the study investigates online information searches and help seeking for mental health problems. Multinomial logistic regressions are estimated for respondents’...
We present a novel face alignment framework based on coarse-to-fine shape searching. Unlike the conventional cascaded regression approaches that start with an initial shape and refine the shape in a cascaded manner, our approach begins with a coarse search over a shape space that contains diverse shapes, and employs the coarse solution to constrain subsequent finer search of shapes. The unique stage-by-stage...
Research on individual ecommerce has suggested that digital divide hinders potential consumers to adopt its utilization in spite of their availability. This article investigates the determinants of digital divide in individual ecommerce utilization in the Chinese context. The study focuses on two types of effects at the individual level: the first order digital divide in access to Internet and the...
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