Autoencoding Blade Runner: reconstructing films with artificial neural networks
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Re: Autoencoding Blade Runner: reconstructing films with artificial neural networks
#2Re: Autoencoding Blade Runner: reconstructing films with artificial neural networks
#3Re: Autoencoding Blade Runner: reconstructing films with artificial neural networks
#4I guess I feel like there's no practical result here. It's only interesting from an aesthetic point of view.
Am I being unfair?
Re: Autoencoding Blade Runner: reconstructing films with artificial neural networks
#5Now back to the article, can someone explain about how many passes before it gets to near film quality? Can it extrapolate missing frames eventually?
Re: Autoencoding Blade Runner: reconstructing films with artificial neural networks
#6Very interesting. This makes me wonder if a similar technique can be used for compression?
Re: Autoencoding Blade Runner: reconstructing films with artificial neural networks
#7Re: Autoencoding Blade Runner: reconstructing films with artificial neural networks
#8What is the difference between using a neural network to do this and using a filter that obtains the same or similar effect by distorting the frames of the input randomly? I guess I feel like there's no practical result here. It's only interesting from an aesthetic point of view. Am I being unfair?
If they're trying to create interesting swirly stuff, where do they intend to go after that?
I mean, sure it's aesthetic though not on the level of weirdness of deep dreams modification.
Re: Autoencoding Blade Runner: reconstructing films with artificial neural networks
#9Would be interesting if somebody one of these days can actually reconstruct to a high level of fidelity what our brain is "seeing".. I bet it would look kind of like this..
Re: Autoencoding Blade Runner: reconstructing films with artificial neural networks
#10Correct me if I haven't looked into this closely, but one glaring problem is that all the results are from the training set. So it's not surprising you get something movie-ish by running the network over a movie it was trained on ; the network has already seen what the output of the movie should look like.