Research @ Mangaki Recommandation d'anime et de mangas

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AI for Manga & Anime (AIMA)

We are pleased to give a keynote at the Anime Expo conference in Los Angeles, on July 5!

AI has given rise to AlphaGo and self-driving cars. What about anime? Using deep learning, we can automatically generate the perfect waifu (or husbando) for you, or prioritize your watchlist. Join us for a showcase of amazing research including manga style transfer, automatic colorization, and more!

And here is the current line-up of speakers:

Create Anime Characters using AI

We all love anime characters and are tempted to create our own, but most of us cannot do that because we are not professional artists. AI comes to rescue: on MakeGirlsMoe, you can just specify attributes (such as blonde/twin tailed/smiling) and our deep neural network will generate automatically an anime character at a professional level of quality! Our recent research is targeting style transfer from IRL pictures to manga characters.

Make.Girls.Moe got 1 million views the first 10 days. Our research proceedings were quickly sold out at the Comic Market #92 (Tokyo) in Summer 2017.


MakeGirlsMoeTechnical Report (NIPS Workshop for Creativity & Design)
CrypkoWhite paper

Using Posters to recommend anime and mangas

Everyone regularly ask themselves what movie, series or book they should watch next, according to their taste. Mangaki is a award-winning website that innovates access to Japanese culture through a recommender system. When a user shows up, our algorithm asks them to rate a few works. Based on their answers, they receive a personalized to-watch list of anime & manga, by geometrically positioning their ratings within those collected from other users, and using deep learning to extract information from manga covers or anime posters.

Mangaki gathered 330k ratings from 2,000 people over 11,000 anime & manga works. In Summer 2017, we released them for a data challenge organized by Kyoto University that attracted 31 submissions from 11 countries. Mangaki was awarded the first prize by the Japan Foundation (Paris branch), and an open source award by Microsoft Ventures.

Tool: Illustration2Vec by Yusuke Matsui
MangakiPress release – Technical report: the BALSE algorithm

Automatic Manga Colorization


PaintsTransfer + GitHub


PaintsChainer by PFN

Manga Style Transfer

Cross-Domain Translation of Human Portraits.

Manga style transfer

Slide from Yanghua Jin’s presentation Creating Anime Characters with GAN at the Tokyo Deep Learning Workshop held in RIKEN AIP on March 21, 2018.

Blog post about TwinGAN

Don’t miss it!