> Instead of using a DCT to generate a new bit representation like many compression schemes in use today, we train two sets of neural networks - one to create the codes from the image (encoder) and another to create the image from the codes (decoder).
So instead of implementing a DCT on my client I need to implement a neural network? Or are these encoder/decoder steps merely used for the iterative "encoding" process? It seems like the representation of a "GRU" file is different from any other.
It sounds complicated, but neural networks these days are basically just a bunch of filters with nonlinear cut-off and bining. (From a signal processing point of view..)
Super simple to implement the feed-forward scenario for decoding.
Not entirely sure what the residual memory aspect of these networks add in terms of complexity, but it's probably just another vector add-multiply, or something to that effect.
Yes you would. But if this becomes widely used you would expect the decode portion to distributed to work on a variety of platforms. Just like jpeg is today. Although I dont think this going to happen. If they can do the same for video, leveraging temporal correlations, then I can see it taking off. In this case the decode neural network would be embedded in the codec.
So instead of implementing a DCT on my client I need to implement a neural network? Or are these encoder/decoder steps merely used for the iterative "encoding" process? It seems like the representation of a "GRU" file is different from any other.