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The mission of our lab is to develop the cutting-edge computer vision and machine (deep) learning algorithms. In particular, our lab is focusing on the various computer vision applications including 3D pose estimation and action/gesture recognition of human bodies, faces and hands, 3D reconstruction of objects and scenes, scene and object recognition. We are also concerning about the insufficient data issues in computer vision problem and try to solve it via synthesizing realistic data using GAN, self-supervision, weakly supervised learning, active learning, domain adaptation methods.
Major research field
Computer Vision and Machine (Deep) Learning
Desired field of research
3D Pose estimation and action/gesture recognition, 3D scene and object reconstruction and recognition
Research Keywords and Topics
· Computer Vision
· Deep/Machine Learning
· Pose Estimation of Human Body, Face and Hand
· Action and Gesture Recognition
· Semantic Segmentation
· Object Recognition
Research Publications
• Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA (Oral presentation, 5.7% Accept ratio) / Weakly-supervised Domain Adaptation via GAN and Mesh Model for Estimating 3D Hand Poses Interacting Objects / Seungryul Baek, Kwang In Kim, Tae-Kyun Kim / 2020
• Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Long Beach, CA, USA / Pushing the envelope for RGB-based dense 3D hand pose estimation via neural rendering / Seungryul Baek, Kwang In Kim, Tae-Kyun Kim / 2019
• Proc. of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, USA (Oral presentation, 2.1% Accept ratio) / Augmented skeleton space transfer for depth-based hand pose estimation / Seungryul Baek, Kwang In Kim, TaeKyun Kim / 2018
국가과학기술표준분류
- EE. 정보/통신
- EE01. 정보이론
- EE0108. 인공지능
국가기술지도분류
- 정보-지식-지능화 사회 구현
- 012300. 인공지능/지능로봇 기술
녹색기술분류
- 녹색기술관련 과제 아님
- 녹색기술관련 과제 아님
- 999. 녹색기술 관련과제 아님
6T분류
- IT 분야
- 정보처리 시스템 및 S/W
- 010314. 신호처리기술(영상/음성처리/인식/합성)