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Perceptual loss for light field reconstruction in high-dimensional convolutional neural networks

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Abstract

We explore the benefits of perceptual loss for light field (LF) spatial recon struction in a high-dimensional convolutional neural network. The results outperform some state-of-the-art methods for LF or image super-resolution.

© 2019 The Author(s)

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