weeb_throwaway

This list is similar: https://github.com/dimpurr/awesome-acg-machine-learning

It has a bit more focus on manga datasets like http://www.manga109.org/en/index.html

Tentacles.

You couldn't have discovered it as a fetish through scientific experimentation. It probably wasn't one until it was used to bypass japanese censorship laws which also accidentally conditioned the popular psyche to associate it with porn.

There are still a lot of ongoing breakthroughs of this kind in hentai. For example the genre of monster/anthropomorphic girls is currently exploding. I recently beat my meat to a world war 2 battleship in the shape of a girl.

Selection bias is also apparent in ranking sites for shows where seasons/sequels are ranked individually.

For example in anime, Gintama appears 8 times within the top 50: https://myanimelist.net/topanime.php

It's not because it's a popular show. It's just that people who didn't like the first few episodes have already stopped watching! And it's polarizing enough that the only people who stick around for so many seasons are the ones really love it. So it will get rated a 10 even for mediocre content.

This barely scratches the complexity of IMEs. For example Hong Kong mainly speak a different dialect of chinese, Cantonese. So pinyin (mandarin phonetics) is useless.

Most people type with Cangjie instead: https://en.wikipedia.org/wiki/Simplified_Cangjie

Another issue with CJK is vertical right-to-left writing: https://www.w3.org/International/articles/vertical-text/

It's pretty popular with japanese novels/manga and traditional chinese but really hard to do without bugs on the web.

I think I refused to believe it too until reddit, a San Francisco company, started banning people for posting fictional high school anime characters in bikinis (not even nudes).

I don't know danbooru, but on another nsfw japanese comic site, 11500 of the 61973 english translated works are tagged as lolicon. Majority of the remaining are teenagers at best (because most anime are in a high school setting).

So you're not crazy. These are really young looking. It is probably just representative of the dataset. The dataset itself wasn't chosen for any malicious reason, the people who like this stuff just happen to be very prolific artists so there's a machine learning scale amount of it.

I saw the section about not training from scratch (via transfer learning) in https://www.gwern.net/Faces#transfer-learning. The Holo example is really impressive!

How expensive is it in terms of labelled data and compute? Do you know if anyone tried this for just ahegao faces?

I am trying out the app at https://waifulabs.com/ and the art style is kind of one-note. Most of the expressions are the same and the face shape skews towards loli.

I am more into "disgusted anime girl that looks at you like you're trash" type and I couldn't find a waifu (even with their refinement steps).

Really impressed that this is even possible though!