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We present a novel method to recover images of faces, particularly when large spatial regions of the face are unavailable due to data losses or occlusions. In contrast with previous work, we do not make assumptions on the data neither during training nor testing (such as assuming that the person was seen before or that all faces are perfectly aligned and have identical head pose, expression, etc.)...
This paper describes new image prediction methods based on neighbor embedding (NE) techniques. Neighbor embedding methods are used here to approximate an input block (the block to be predicted) in the image as a linear combination of nearest neighbors. However, in order for the decoder to proceed similarly, the nearest neighbors are found by computing distances between the known pixels in a causal...
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