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In this paper, we present a novel method to super-resolve and recover the facial depth map nicely. The key idea is to exploit the exemplar-based method to obtain the reliable face priors from high-quality facial depth map to improve the depth image. Specifically, a new neighbor embedding (NE) framework is designed for face prior learning and depth map reconstruction. First, face components are decomposed...
The simple yet subtle structures of faces make it difficult to capture the fine differences between different facial regions in the depth map, especially for consumer devices like Kinect. To address this issue, we present a novel method to super-solve and recover the facial depth map nicely. The key idea of our approach is to exploit the learning-based method to obtain the reliable face priors from...
In this paper, we propose a novel autoregressive (AR) model based on the adaptive window and the patch-geodesic distance for the image interpolation. The model combines the information of inner/inter-patch correlation. To model the inner-patch correlation, we introduce a patch-geodesic distance similarity metric. The proposed metric shows the desirable capacity to depict the piecewise-stationarity...
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