https://en.wikipedia.org/wiki/Abstraction-Filtration-Compari...
Will that test be applied here?
Does it need to be revised in light of deep learning?
61–70 of 70 posts
https://en.wikipedia.org/wiki/Abstraction-Filtration-Compari...
Will that test be applied here?
Does it need to be revised in light of deep learning?
This is the original article by Terrence Broad: https://medium.com/@Terrybroad/autoencoding-blade-runner-889... and its appearance on HN the other week: https://news.ycombinator.com/item?id=11766063
This article alludes to, but never actually brings up, something much more interesting than the project in question: How can copyright coexist with human-level automatic analysis and synthesis of works of art? For example, Spotify is flooded with "covers" of hit songs that are made to sound as similar to the original as possible. In my understanding, it doesn't matter how similar it sounds, as long as it's "remade",…
It basically points out that even shot-for-shot remakes are violating various copyrights, especially the copyright for the screenplay.
Bullshit... this is still encoding. It does not matter that it is using neural network to encode frame. Guys, when you get over this neural network hype? I can as well create and encoder using some machine learning, to create a blurry and inferior version of the movie. But what's the point? I could as well used other prediction method with some kind of memory, much superior and nobody will enjoy it. Summing up: nothi…
> But what's the point? Autoencoders don't really have much practical use now, but that's not the point of them. The point is we really want to figure out how to do unsupervised learning well and autoencoders are one of the few ways of doing it. We want to do unsupervised learning well because most learning that humans do is unsupervised. The idea behind autoencoding is that by forcing the network to try to learn eff…
The worst part about this encoder is it thinks it's dealing with static pictures in plenty of cases. The version on the right simply has no movement while movie continues to play on left. Also, faces don't move when one person speaks. That's a no go even if the picture quality didn't look like crap.
If you were actually using this for compression, this could be useful.You could store the "diff" between the reconstruction and the actual pixels, which would take many fewer bits than storing the whole image. Video compression already does something like this, storing a frame, and then the following frames just being diffs to the pixels of the previous frame.
The goal of this project seems to be more artistic, so the poor quality might even be desirable.
The worst part about this encoder is it thinks it's dealing with static pictures in plenty of cases. The version on the right simply has no movement while movie continues to play on left. Also, faces don't move when one person speaks. That's a no go even if the picture quality didn't look like crap.
It depends what your goal is. This is quite impressive for compressing each image down to 200 bytes. If you were actually using this for compression, this could be useful.You could store the "diff" between the reconstruction and the actual pixels, which would take many fewer bits than storing the whole image. Video compression already does something like this, storing a frame, and then the following frames just being…
Earlier quoted context omitted.
This is possibly the next generation of video/audio/image codecs. What he did was create a specialized compression algorithm that works very well to compress the data that is each frame of Blade Runner, and decompress it (lossily, like mp3) back into a video stream. To put this into perspective: Blade Runner is 117 minutes long. At 25 frames per second, that is 175_500 frames. As he says, the input data he used was 2…
"with compressors that can are so good for one specific set of data that compressor + data is smaller than anything the traditional compressors could create." This is well, hopeful but probably wrong ... because we already know how to make it smaller for this type of data. The algorithms used for interframe/intraframe prediction are chosen to tradeoff speed vs size. If you built a really large-scale predictor that wa…
And it doesn't need to work on every frame, it could pump out I-frames every 15 seconds or so.
Earlier quoted context omitted.
This is possibly the next generation of video/audio/image codecs. What he did was create a specialized compression algorithm that works very well to compress the data that is each frame of Blade Runner, and decompress it (lossily, like mp3) back into a video stream. To put this into perspective: Blade Runner is 117 minutes long. At 25 frames per second, that is 175_500 frames. As he says, the input data he used was 2…
Except that in my understand, the decoded version looks like shit. So, while optimistic that this technology might be quite good eventually, more heuristics are probably needed for the right way to extract an optimal encoding. e.g. see the screenshots here: http://www.eteknix.com/blade-runner-gets-trippy-auto-encoded...
Earlier quoted context omitted.
It depends what your goal is. This is quite impressive for compressing each image down to 200 bytes. If you were actually using this for compression, this could be useful.You could store the "diff" between the reconstruction and the actual pixels, which would take many fewer bits than storing the whole image. Video compression already does something like this, storing a frame, and then the following frames just being…
It's not impressive to get an image small if you delete a bunch of critical stuff out of it plus warp what remains. Ill agree on the art project part, though.
Earlier quoted context omitted.
It's not impressive to get an image small if you delete a bunch of critical stuff out of it plus warp what remains. Ill agree on the art project part, though.
What do you expect from compressing an image to 200 bytes? It's impressive that it has as much detail as it does.