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Found 7 papers, 3 papers with code
Painting Style-Aware Manga Colorization Based on Generative Adversarial Networks
To realize consistent colorization, we propose here a semi-automatic colorization method based on generative adversarial networks (GAN); the method learns the painting style of a specific comic from small amount of training data.
Towards Fully Automated Manga Translation
We are the first to incorporate context information obtained from manga image.
Learning to Describe Unknown Phrases with Local and Global Contexts
When reading a text, it is common to become stuck on unfamiliar words and phrases, such as polysemous words with novel senses, rarely used idioms, internet slang, or emerging entities.
Learning to Describe Phrases with Local and Global Contexts
When reading a text, it is common to become stuck on unfamiliar words and phrases, such as polysemous words with novel senses, rarely used idioms, internet slang, or emerging entities.
A Bag of Useful Tricks for Practical Neural Machine Translation: Embedding Layer Initialization and Large Batch Size
In this paper, we describe the team UT-IIS{'}s system and results for the WAT 2017 translation tasks.
Chunk-based Decoder for Neural Machine Translation
The chunk-level decoder models global dependencies while the word-level decoder decides the local word order in a chunk.
