3차원 비쥬얼 컴퓨팅 및 기하학적 처리 연구실

3D information is widely used for perception, and recent trends on 3D perception utilize the state-of-the-art techniques from computer vision and machine learning. We utilize neural networks of generative models, metric learning, and/or reinforcement learning to boost the performance. We sense, model, and understand the geometric structure around us. The geometric structure stems from the physical space we live in, and we utilize the information to better combine knowledge and embed technology within the relationship between objects and humans. To do this, we adapt the state-of-the-art techniques from computer graphics, computer vision, machine learning, and robotics. The ultimate goal is to embrace the technology to seamlessly augment the limitation of time, space, or human, and make a better world.