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Found 3 papers, 1 papers with code
Content-oriented learned image compression
In recent years, with the development of deep neural networks, end-to-end optimized image compression has made significant progress and exceeded the classic methods in terms of rate-distortion performance.
Hierarchical Image Compression Framework
In learning-based image compression approaches, compression models are based on variational autoencoder(VAE) framework and optimized by a rate-distortion objective function, which achieve better performance than hybrid codecs.
Asymmetric Gained Deep Image Compression With Continuous Rate Adaptation
With the development of deep learning techniques, the combination of deep learning with image compression has drawn lots of attention.
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