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Or low connectivity scenarios that pushes more local processing.

I think it a bit unimaginative to see no use cases for this.

There is no use case, because it is a stupid idea. Downscaling then reconstructing is a stupid idea for exactly the same reasons why downscaling for compression is a bad idea.

The issue isn't NN reconstruction, but that you are reconstructing the wrong data.

if the nn is part of the codec, you can choose to only downscale the regions that get reconstructed correctly.

Why would you not let the NN work on the compressed data? That is actually where the information is.

that's like asking why you don't train a llm on gzipped text. the compressed data is much harder to reason about

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