Method and apparatus for rate-adaptive neural image compression with adversarial generators
Abstract:
A method of rate-adaptive neural image compression with adversarial generators is performed by at least one processor and includes obtaining a first feature of an input image, using a first portion of a first neural network, generating a first substitutional feature, based on the obtained first feature, using a second neural network, and encoding the generated first substitutional feature, using a second portion of the first neural network, to generate a first encoded representation. The method further includes compressing the generated first encoded representation, decompressing the compressed representation, and decoding the decompressed representation, using a third neural network, to reconstruct a first output image.
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