We are tackling fundamental problems in computer vision and graphics to achieve a deep understanding of visual information in the world.
Our main challenge in the computer vision domain is divided into two categories: generative and discriminative. Image generation tasks aim to create (or convert) an image reflecting the semantics of the given condition. The representative tasks are image-to-image translation, image colorization, image in-painting and video generation. The discriminative problem tries to compress an image into low-dimensional representation while preserving its essential information. It contains visual representation learning, label propagation, segmentation, and video understanding.