It's copy-pasting parts of the training images over and over.
In figure 8 of the technical report [0], compare the hair in images (0,0), (2,0), (3,0), (3,3), (4,4).
The paper suggests their method generates copyright-free images, yet they are very obviously derived from the input images and you can identify the parts of individual input images that are mashed together to form the output.
All in all their method seems to be performing "obfuscated memorization," in the sense that the generated images are scrambled up enough to fool their plagiarsim-detector loss function.
But as the online article states, that figure represents a case where the model is explicitly set to "generate images [which] have similar major visual features with different attribute combinations": http://make.girls.moe/#/news
So some degree of repetition is to be expected, since you've turned off random noise. And despite that the images do still exhibit some variation if you look closely.
For the uninitiated: (form Wikipedia) Moe (萌え, pronounced [mo.e]) is a Japanese slang loanword that refers to feelings of strong affection mainly towards characters in anime, manga, and video games.
By the way, the Getchu and illustration2vec links on the news page are broken.
Edit: This part from the Tips page might be why it initially didn't generate great images:
The input of the model consists of two parts, the random noise part and the condition part. If you generate a good image, you could try to fix the noise part and use random conditions to get more good images. We have observed that a good random noise is important for the better generation.
Edit 2: Actually, no. According to the news page, if the noise is fixed, the generated pictures would be all similar.
Well, "make.girls.moe" is the URL and name of the tool.
According to the technical report [1], they used character portraits from Getchu [2] for training data. A cursory glance shows that the overwhelming majority of the characters are female. As a result, the characters the tool generates are likely to appear female to our eyes.
After the code is open sourced, perhaps someone should try to create make.boys.moe using character portraits from otome games [3].
Please don't propagate that sexist, binary view on gender. If you make the effort to criticise non-equal treatment, please always also include genderless, non-binary bigender or trigender, pangender, trans woman, trans man and any other-gendered.
[+] [-] duj|8 years ago|reply
In figure 8 of the technical report [0], compare the hair in images (0,0), (2,0), (3,0), (3,3), (4,4).
The paper suggests their method generates copyright-free images, yet they are very obviously derived from the input images and you can identify the parts of individual input images that are mashed together to form the output.
All in all their method seems to be performing "obfuscated memorization," in the sense that the generated images are scrambled up enough to fool their plagiarsim-detector loss function.
[0] http://make.girls.moe/technical_report.pdf
[+] [-] yohui|8 years ago|reply
But as the online article states, that figure represents a case where the model is explicitly set to "generate images [which] have similar major visual features with different attribute combinations": http://make.girls.moe/#/news
So some degree of repetition is to be expected, since you've turned off random noise. And despite that the images do still exhibit some variation if you look closely.
[+] [-] indescions_2017|8 years ago|reply
For the uninitiated: (form Wikipedia) Moe (萌え, pronounced [mo.e]) is a Japanese slang loanword that refers to feelings of strong affection mainly towards characters in anime, manga, and video games.
http://nic.moe/en/
[+] [-] ReverseCold|8 years ago|reply
[+] [-] ue_|8 years ago|reply
[+] [-] King-Aaron|8 years ago|reply
[+] [-] navs|8 years ago|reply
[+] [-] asr1191|8 years ago|reply
And short hair seems to produce male characters
[+] [-] theemathas|8 years ago|reply
By the way, the Getchu and illustration2vec links on the news page are broken.
Edit: This part from the Tips page might be why it initially didn't generate great images:
The input of the model consists of two parts, the random noise part and the condition part. If you generate a good image, you could try to fix the noise part and use random conditions to get more good images. We have observed that a good random noise is important for the better generation.
Edit 2: Actually, no. According to the news page, if the noise is fixed, the generated pictures would be all similar.
[+] [-] hiepph|8 years ago|reply
[+] [-] hatsunearu|8 years ago|reply
[+] [-] hardmaru|8 years ago|reply
[+] [-] hatsunearu|8 years ago|reply
I thought DNN models are fucking huge?
[+] [-] codedokode|8 years ago|reply
In Cromium 46 (released in 2015) there is an error:
> Error during service worker registration: DOMException: Only secure origins are allowed (see: https://goo.gl/Y0ZkNV).(anonymous function) @ main.4188687f.js:1 descriptor_runner_webassembly.ts:172 ErrorEvent {isTrusted: true}worker.onerror @ descriptor_runner_webassembly.ts:172
> Uncaught RangeError: Invalid array buffer length math.ts:55 Model loading failed for webassembly backend. Trying next backend: Uncaught RangeError: Invalid array buffer length
In Firefox 45 (released in 2015) there is an error
> InternalError: uncaught exception: out of memory
(the necessary amount of memory is not reported)
[+] [-] brudgers|8 years ago|reply
[+] [-] mollusk|8 years ago|reply
[+] [-] grondilu|8 years ago|reply
[+] [-] mindw0rk|8 years ago|reply
[+] [-] ldjb|8 years ago|reply
[+] [-] jacquesm|8 years ago|reply
[+] [-] yohui|8 years ago|reply
According to the technical report [1], they used character portraits from Getchu [2] for training data. A cursory glance shows that the overwhelming majority of the characters are female. As a result, the characters the tool generates are likely to appear female to our eyes.
After the code is open sourced, perhaps someone should try to create make.boys.moe using character portraits from otome games [3].
[1]: 12.8 MB PDF, http://make.girls.moe/technical_report.pdf
[2]: example from report (possibly NSFW?), http://www.getchu.com/soft.phtml?id=933144
[3]: games with a female protagonist and many male characters, https://vndb.org/g542
[+] [-] chobytes|8 years ago|reply
[+] [-] thowfaraway|8 years ago|reply
[+] [-] sanxiyn|8 years ago|reply
[+] [-] tatami|8 years ago|reply
[+] [-] type-2|8 years ago|reply
[+] [-] unknown|8 years ago|reply
[deleted]
[+] [-] aw3c2|8 years ago|reply
[+] [-] shp0ngle|8 years ago|reply
[+] [-] redwhitemiko|8 years ago|reply