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Generating faces of cats using Generative Adversarial Networks
- threepipeproblm 9y agoI was expecting meows.
- phs2501 9y agoYeah, that would have been more interesting. This is technically a meow generator generator.
- deleted 9y ago[deleted]
- dredmorbius 9y agohttp://discuss.joelonsoftware.com/default.asp?joel.3.219431.12 http://discuss.joelonsoftware.com/default.asp?joel.3.219431....
- BinaryBullet 9y agonot meows, but here are some purrs: https://purrli.com/ https://purrli.com/
- ovrdrv3 9y agoOP's post was amazing but can someone explain how this was probably made?
- audiosampling 9y agoMeow-generator when the last slider is set to Meow-y ;-)
- E6300 9y agoIt's a shame that the meows in the "meow-y" setting are just regular meows, not purry meows (as in, meowing and purring simultaneously).
- jpindar 9y agohere's some more purrs: https://mynoise.net/NoiseMachines/catPurrNoiseGenerator.php https://mynoise.net/NoiseMachines/catPurrNoiseGenerator.php
- syntheticnature 9y agoI'll admit I too was expecting cat-centric "speech" synthesis.
- deleted 9y ago[deleted]
- threepipeproblm 9y agoDid you try clicking on the cat faces to see if they meowed? Not a proud confession here. BTW this is a cool project even without the audio.
- ryall 9y agoIf it's meows you want, have I got the album for you! http://pitchfork.com/reviews/albums/21145-meow-the-jewels/ http://pitchfork.com/reviews/albums/21145-meow-the-jewels/
- deleted 9y ago[deleted]
- cctan 9y agoI too was expecting meow purr audio content generation when I clicked into the link haha.
- waqf 9y agoWith this kind of task, how do you verify that you didn't just overfit and start reproducing the input data?
- kowdermeister 9y agoShe's generating it from noise: https://github.com/AlexiaJM/Deep-learning-with-cats/blob/master/images/DCGAN_220epochs.gif https://github.com/AlexiaJM/Deep-learning-with-cats/blob/mas... Also, you could verify by writing unit tests with OpenCV to look for similar sources. Since it's all headshots, it will find matches for sure, but it would also find with human faces.
- semiquaver 9y agoThe neural network is starting from noise, but that's not the only input, it was trained on [0] and I think it's arguable that the NN is "reproducing" the images from its training dataset in some sense. [0] https://web.archive.org/web/20150703060412/http://137.189.35.203/WebUI/CatDatabase/catData.html https://web.archive.org/web/20150703060412/http://137.189.35...
- highd 9y agoYep, this is a current area of research for content generation. I think most current approaches build some transform to a latent space and then compare generated images with their nearest neighbors in the training set. If they're identical then your network just learned to reproduce the dataset.
- radarsat1 9y agoI think it's a very interesting question, of how can we measure when a neural network is being creative? In fact, creativity is not obvious at all. It's sort of an ill-posed question if you think about it. How can you verify that a network is generating things that are not like what it was trained on, yet are... like what it was trained on? Are neural networks* forever relegated to the role of copying and interpolation? Do the neural network weights form a kind of database? * (I don't think this only applies to neural networks, but models in general) There was one recent work trying to address this [1] but I'm not 100% convinced and I think a lot more work is warranted in this area. A difficulty is that it's not a purely technical problem, but also one of semantics and interpretation. It's one that the "automatic musical accompaniment" community and other digital arts communities have struggled with for decades, and it's not resolved. How do you know when a machine is being creative? It's not far from the moving goalposts problem of general artificial intelligence. How do you know when a machine is being intelligent, if you can always explain it away by examining the black box? [1]: https://arxiv.org/abs/1706.07068 https://arxiv.org/abs/1706.07068
- lostgame 9y agoChange the title? Seems like I wasn't the only one expecting some sort of audio-related thing.
- ChristianBundy 9y agoYeah, I put on headphones for this. Seems like a cat generator.
- aleju 9y agoI would assume that the name was chosen, because I already have an old project online called "cat generator" [0], which used the same underlying technique (GANs), dataset and landmark-based normalization. Reusing the name would have resulted in confusion. [0] https://github.com/aleju/cat-generator https://github.com/aleju/cat-generator
- dschu 9y agoYet another cat generator then (:
- sctb 9y agoAlright, we've updated the title from “Meow Generator”.
- JohnStrange 9y agoThis is maybe the most important question for mankind that has ever been asked, so let me ask it: Would it also be possible to use this method to generate new images of attractive, half-naked female humans on the basis of an existing database of such images?
- dang 9y agoPlease don't do this here.
- JohnStrange 9y agoWhy not? Because of extreme nipple fear? It would most likely be the #1 application of this technique if it worked in general.
- olleromam91 9y agoSounds like a great way to create even more unrealistic standards for beauty. Just a thought.
- dang 9y agoNo, it's because the cost it inflicts on the commons exceeds the benefit of an adolescent sex joke. If we get lots of the the latter, it will turn off and drive away some of the people we want here. Then more good users may start to leave as more good users start to leave—a vicious circle which it's basically our #1 job to (try to) make sure HN doesn't get caught in. So we're a bit hypervigilant about this.
- Zarkonnen 9y agoSomeone did this, kinda, by inverting Yahoo's nudity detection network. The results were, uh, unsettling. https://news.ycombinator.com/item?id=12756462 https://news.ycombinator.com/item?id=12756462
- krick 9y agoIgnoring the joke, this is actually interesting question to ask. I mean, yeah, there are some pretty scary, uncanny images of cats here, but some cats look almost… fine? So if these cat images are "creative" enough — this is almost a success. But if you take a pencil and try to draw a cat yourself (assuming you are not a good artist) you have much higher chances to actually draw something "cute", than if you'd try to draw a woman. Human females look much more familiar, and there's something much trickier and more intimate to what you recognize as "cute" or "beautiful" in a human, than in a cat. So, I'm pretty sure this NN would fail, but it's interesting what's actually required for it to not fail.
- Zenbit_UX 9y agoWait, it's actually generating new cat faces as in cats that don't exist? Some of those images looked like they had backgrounds in the corners was that also generated???
- robotresearcher 9y agoYes.
- leeoniya 9y agowelp, that's terrifying.
- bluetwo 9y agoStill no cure for cancer.
- dboreham 9y agoRead that as "Generating the feces of cats.." which would have been altogether more interesting a problem.
- baybal2 9y agoA dream of cat video clickfarmers came true
- Paul-ish 9y agoThese things are always low resolution. At some point I'd like to see the state of the art move into more realistic (say ~500x500) dimensions.
- alexcnwy 9y agoI think it's in part due to the content loss piece being done using pre-trained imagenet models which typically resize images to 224x224...
- gwern 9y agoThat's not it. It's easy to scale a larger image down to 224x224 and feed it into a checkpoint. And a lot of these GANs don't use such content losses in the first place because it adds complexity and makes it harder to use (have to get one of those pretrained models in the first place).
- deleted 9y ago[deleted]
- gwern 9y agoIt's a combination of GPU RAM, slowdowns (remember it's squared in dimensions), and stability (larger is more unstable end-to-end). Arguably, state of the art in image synthesis is DeepMind's PixelCNN: "Parallel Multiscale Autoregressive Density Estimation" https://arxiv.org/abs/1703.03664 https://arxiv.org/abs/1703.03664 , Reed et al 2017: generating 512px photorealistic images & video with PixelCNNs rather than GANs. Also good is StackGAN which does ~200x200ish but there's no reason it couldn't go up to 500x500 (just pop in a third upscaling stage). There's far more work on GANs than PixelCNNs (see the https://github.com/hindupuravinash/the-gan-zoo https://github.com/hindupuravinash/the-gan-zoo ) but at least thus far, I haven't seen any GANs which appear visually competitive with Reed et al 2017's PixelCNN samples. Downside - code has not been released by DeepMind[], and you can't do CycleGAN or other stupid GAN tricks with PixelCNN AFAIK. CycleGAN is absolutely hilarious, if you haven't seen all the uses of it yet, much more interesting than generating cat faces. [] I asked way back when and Reed said he'd try but nothing yet.
- nilkn 9y agoWhat are some potential applications of this outside of toy problems like cat pictures?
- 6502nerdface 9y agoGenerating convincing profile pictures for thousands of fake social media accounts. Or photo portraits of the "board members" for the About Us page of an autonomous corporation.
- clock_tower 9y agoI expect it could stretch a game's art budget considerably, FWIW...
- Jack000 9y agogenerating tween frames for animation