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This paper proposes a new high dimensional regression method by merging Gaussian process regression into a variational autoencoder framework. In contrast to other regression methods, the proposed method focuses on the case where output responses are on a complex high dimensional manifold, such as images. Our contributions are summarized as follows:...
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... estimated the 100 images in the test set by using their domain information only, and compared the similarity between the ground truth image and the regression results. Table 1 shows the performance mea- Table 2. Measure for images from +0.5σ, +1.0σ and +1.5σ. ...Similar publications
Image-to-image translation aims to learn the mapping between two visual domains. There are two main challenges for this task: (1) lack of aligned training pairs and (2) multiple possible outputs from a single input image. In this work, we present an approach based on disentangled representation for generating diverse outputs without paired training...
