We proposed and experimented on multiple conditional Generative Adversarial Networks models for colorizing line art based on the given color hints by the user.

We defined an interface (gyms environment) to SUMO so that modeling of automated driving can be done using inter-vehicle communication and reinforcement learning, and verified that the interface works by conducting reinforcement learning experiments.

WaveNet has achieved high accuracy in the Text-To-Speech task. We hypothesized and experimented that it may perform well in chart-generation task.

I applied reinforcement learning to NetHack in order to learn strategies. I proposed the model for this purpose and confirmed its effectiveness.

We introduced LoL-V2T: a large video-to-text dataset and generated captions for esports footage with deep learning.

We propose a combination of 3 deep learning models to estimate the key which you want to press based on the hand poses which is taken with one RGB camera.