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Generative 3D face models are a powerful tool in computer vision. They provide pose and illumination invariance by modeling the space of 3D faces and the imaging process. The power of these models comes at the cost of an expensive and tedious construction process, which has led the community to focus on more easily constructed but less powerful models. With this paper we publish a generative 3D shape...
This paper presents a novel framework to localize in a photograph prominent irregularities in facial skin, in particular nevi (moles, birthmarks). Their characteristic configuration over a face is used to encode the person's identity independent of pose and illumination. This approach extends conventional recognition methods, which usually disregard such small scale variations and thereby miss potentially...
Unconstrained illumination and pose variation lead to significant variation in the photographs of faces and constitute a major hurdle preventing the widespread use of face recognition systems. The challenge is to generalize from a limited number of images of an individual to a broad range of conditions. Recently, advances in modeling the effects of illumination and pose have been accomplished using...
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