Welcome to GIP LAB
Computer Graphics & Image Processing Laboratory
about us.
We are a research laboratory working on graphics, computer vision and image processing.
In the field of graphics, we are studying the latest graphics library including OpenGL and DirectX in development. we also studying 3D modeling, VR, AR, and MR. If you study graphics, you can apply for 3D related companies, and you will be able to support VR and AR, which are emerging as the fourth industry in recent years.
In computer vision and image processing, we study OpenCV and Deep Learning framework such as Tensorflow, Pytorch, and Keras. In research, we study image related deep learning such as image classification, object detection, and image segmentation. If you study computer vision, you can apply for computer vision and deep learning companies, and many companies will want you in the same way as graphics which is the fourth industry field.
Computer Graphics
- The representation and manipulation of image data by a computer
- The various technologies used to create and manipulate images
- Methods for digitally synthesizing and manipulating visual content

Pixel Art

2D Image

3D Image

Computer Animation
Computer Vision
- Typical Tasks
Recognition
The classical problem in computer vision, image processing, and machine vision is that of determining whether or not the image data contains some specific object, feature, or activity.

Motion analysis
Several tasks relate to motion estimation where an image sequence is processed to produce an estimate of the velocity either at each points in the image or in the 3D scene, or even of the camera that produces the images.

Scene reconstruction
Given one or more images of a scene, or a video, scene reconstruction aims at computing a 3D model of the scene.

Image restoration
The aim of image restoration is the removal of noise (sensor noise, motion blur, etc.) from images.

Deep Learning
Deep learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks have been applied to fields including computer vision and so on.
We mainly use deep learning associated with computer vision.

Contact us

154-42 Gwangkyosan-ro Yeongtong-gu Suwon-si Gyeonggi-do 16227 Republic of Korea.
Room 8501
Professor : Junchul Chun
email : jcchun@kgu.ac.kr
Tel : +82-31-249-9668
Fax : +82-31-253-1165
