Research map / Image generation / Super-resolution
Post-trained Convolution Networks for Single Image Super-resolution (Abstract Reprint)
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Proposes a post-training procedure that updates only the last reconstruction layer of a super-resolution CNN using stochastic dual simplex algorithm (SDSA) and contextual information to improve SISR accuracy.
Problem
Improving the accuracy of state-of-the-art single image super-resolution (SISR) CNNs.
Approach
Post-train an existing SISR CNN by re-optimizing only its last reconstruction layer with the stochastic dual simplex algorithm, using contextual information extracted from the image.
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