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The demo images used on hific.github.io appear to be part of the datasets used to train the system. In another comment you say the trained model is 726MB. The combined size of the training datasets appear to be about 8GB zipped. Is the currently trained model usable on images that are not part of the training datasets? with output of similar quality and size?

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Hi- no the images on the demo page are not part of the training set, they are only used to evaluate the method. Arbitrary images of natural scenes will look similar at these bitrates. We‘ll release trained models and a colab soon!

Thank you and my apologies. I should have read the pdf more carefully where the distinction between the training data and evaluation datasets is described

Our training set consists of a large set of high-resolution images collected from theInternet, which we downscale to a random size between 500 and 1000 pixels, and then randomlycrop to256×256. We evaluate on three diverse benchmark datasets collected independently ofour training set to demonstrate that our method generalizes beyond the training distribution: thewidely usedKodak[22] dataset (24 images), as well as theCLIC2020[43] testset (428 images), andDIV2K[2] validation set (100 images).

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