gtoderici

6 ms·

1.
by gtoderici 6y ago
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, therefore forcing the
2.
by gtoderici 6y ago
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 they're still better.
3.
by gtoderici 6y ago
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
4.
by gtoderici 6y ago
What you suggest has already been done: train a neural network with the output of BPG or JPEG, and ask to reconstruct the input with just the decompressed pixels being available. It definitely is a valid approach but the limitation is that
5.
by gtoderici 6y ago
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 allow the user t
6.
by gtoderici 6y ago
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 be linked from the c
7.
by gtoderici 6y ago
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
8.
by gtoderici 6y ago
(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 make the decod
9.
by gtoderici 6y ago
(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!