Currently, I am working as a research assistant in the C-Design Lab led by Professor Karthik Ramani, focusing on human shape interaction.More Details
COMPUTER VISION / MACHINE LEARNING - deep learning, 3D vision, recognition, tracking
My research interest lies at the intersection of machine learning and computer vision, focusing on computational learning for real-time 3D hand pose estimation. In this area, I have four conference papers in both CVPR and ICCV as a first author, which I solved the vision problems using the machine learning (deep learning) techniques.
Click here to view my CV.
July 2017. Two papers are accepted for publication in IEEE ICCV 2017.
July 2017. I will be attending CVPR 2017.
May 2017. I am joining HERE Technologies as a research intern (deep learning) for summer 2017.
Peer-reviewed Conference Proceedings
C. Choi, S. H. Yoon, C. N. Chen, and K. Ramani, "Robust Hand Pose Estimation during the Interaction with an Unknown Object", In Proceedings of the IEEE International Conference on Computer Vision (ICCV) 2017.
C. Choi*, A. Sinha*, and K. Ramani, "DeepHand: Robust Hand Pose Estimation by Completing a Matrix Imputed with Deep Features", In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2016.
C. Choi, A. Sinha, J. H. Choi, S. Jang, and K. Ramani, "A Collaborative Filtering Approach to Real-time Hand Pose Estimation", In Proceedings of the IEEE International Conference on Computer Vision (ICCV) 2015.
- Specialization: Deep learning, 3D vision, recognition, tracking
- Computational learning for 3D hand pose estimation (first author papers in CVPR and ICCV)
- Committee members: Karthik Ramani (advisor), Stanley H. Chan, Mireille Boutin, Jeffrey M. Siskind
- Specialization: 3D shape analysis (matching and registration)
- Advisor: Prof. Suya You, Department of Computer Science, USC
- Minor: Mechanical Engineeering
- Learning Hand by Hallucinating Geometric Representations
- Learning Hand from a Manipulating Object
- Embedding Compressive Layers in Deep Neural Networks
- Learning Hand from Low-Dimensional Visual Representations
- Learning Hand from Recommendations of Similar Poses
- Real-Time 3D Object Tracking from Depth
- Scale and Rotation Invariant 3D Shape Matching
- Finding Dense Correspondences between 3D Shapes