Not sure how that would work out in practice. We kind of rushed with the experiments in any case - maybe we could let the methods train for longer. In the end the adversary might learn any regular patters that appear,…
Independently of this work, we have models which are competitive with HEVC while being significantly smaller (this is from previous work). They will not look nearly as good as what you see in the website demo, but…
We haven't specifically compared to AVIF, which as far as we know is still under development. We'd be happy to compare, but it's unlikely that we'd learn much out of it. As far as we know, AVIF is better by <100% than…
One of the things we discussed to address this is to have the ability to: a) turn off detail hallucination completely given the same bitstream; and b) store the median/maximum absolute error across the image (b) should…
On the standardization issue: the advantage of such a method that we presented is that as long as there exists a standard for model specification, we can encode every image with an arbitrary computational graph that can…
That was exactly the goal of the project! Basically if the size doesn't allow to have detail, we need to "hallucinate it". This of course is not necessary if there's enough bandwidth available for transmission or enough…
(coauthor here) We used an adversarial loss in addition to a perceptual loss and MSE. None of these work super-well when the others are not used. The adversarial loss "learns" what is a compressed image and tries to…
(coauthor here) The 0.7 megapixels/sec is PNG decode (to get input)+encoding+decoding+PNG encoding (to get output we can visualize in a browser) speed. Thanks for your kind comment!
Not sure how that would work out in practice. We kind of rushed with the experiments in any case - maybe we could let the methods train for longer. In the end the adversary might learn any regular patters that appear,…
Independently of this work, we have models which are competitive with HEVC while being significantly smaller (this is from previous work). They will not look nearly as good as what you see in the website demo, but…
We haven't specifically compared to AVIF, which as far as we know is still under development. We'd be happy to compare, but it's unlikely that we'd learn much out of it. As far as we know, AVIF is better by <100% than…
One of the things we discussed to address this is to have the ability to: a) turn off detail hallucination completely given the same bitstream; and b) store the median/maximum absolute error across the image (b) should…
On the standardization issue: the advantage of such a method that we presented is that as long as there exists a standard for model specification, we can encode every image with an arbitrary computational graph that can…
That was exactly the goal of the project! Basically if the size doesn't allow to have detail, we need to "hallucinate it". This of course is not necessary if there's enough bandwidth available for transmission or enough…
(coauthor here) We used an adversarial loss in addition to a perceptual loss and MSE. None of these work super-well when the others are not used. The adversarial loss "learns" what is a compressed image and tries to…
(coauthor here) The 0.7 megapixels/sec is PNG decode (to get input)+encoding+decoding+PNG encoding (to get output we can visualize in a browser) speed. Thanks for your kind comment!