[lopsidedBrain]

The comparison is fair because it tries to automate expertise.

I'm sure you know exactly how much of which filter to apply for similar results. Laymen like ourselves will need a lot more trial and error. Their contribution here is to provide a push-button, automated mechanism.

I would have probably also tried something simple and given up due to the noise. So this is definitely interesting.

[BubRoss]

This is completely untrue.

What you are describing is usually called automatic tone mapping. This is basically noise reduction and possibly color normalization from brightening a dark image. Them showing their black image as the starting point is silly, because jpg will make a mess of the remaining information. What they should show is the raw image brightened by a straight multiplier to show the noisy version that you would get from trying to increase brightness in a trivial way.

[pera]

What jpg? they are using raw data.

[Jnr]

Image on Github is JPEG made from RAW. Since RAW file has more dynamic range and contains a lot more information than JPEG you can take that photo in an editor and crank up the brightness. You will get a noisy image but it will be a lot brighter and will probably resemble the image with the high ISO in the middle. Then in an editor you can apply some de-noiser to get results similar to the last one.

So presumably this neural net more or less does it for you.

[pera]

The *PNG is there just to show the results produced by the CNN, if you watch the linked video they do exactly what you are suggesting and then compare both results.

[BubRoss]

Their example on their github page uses a jpg that makes it look like they are creating something from nothing.