Image Compression is an application of data compression for digital images to lower their storage and/or transmission requirements.
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As far as we know, this is the first neural network architecture that is able to outperform JPEG at image compression across most bitrates on the rate-distortion curve on the Kodak dataset images, with and without the aid of entropy coding.
We introduce a simple and efficient lossless image compression algorithm.
We present a learned image compression system based on GANs, operating at extremely low bitrates.
We fully exploit the hierarchical features from all the convolutional layers.
Ranked #1 on Color Image Denoising on Kodak24 sigma30
We propose the first practical learned lossless image compression system, L3C, and show that it outperforms the popular engineered codecs, PNG, WebP and JPEG 2000.
Ranked #2 on Image Compression on ImageNet32