Personal profile

Research interests

I am interested in machine learning, computer vision, computer graphics, and human-computer interaction.

My current research interests focus on mining, processing, and displaying image and video data. I have also worked on modeling and enhancement of images and video, especially in the context of denoising, artifact removal, super-resolution, and deblurring and on algorithmic aspects of machine learning including semi-supervised learning, sparse Bayesian inference, and link-prediction in graphs.

Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

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Projects 2015 2020

Research Output 1999 2018

Augmented Skeleton Space Transfer for Depth-based Hand Pose Estimation

Baek, S., Kim, K. I. & Kim, T. K. 19 Feb 2018 Proc. CVPR.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Discriminators
Byproducts
Data acquisition
Cameras
Availability

High-order Tensor Regularization with Application to Attribute Ranking

Kim, K. I., Park, J. & Tompkin, J. 19 Feb 2018 Proc. CVPR.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Higher-order tensor
Tensor
Attribute
Riemannian manifold
Euclidean space

Multi-task Learning by Maximizing Statistical Dependence

Alami Mejjati, Y., Cosker, D. & Kim, K. I. 19 Feb 2018 Proceedings of CVPR.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Random variables
Neural networks

Criteria Sliders: Learning Continuous Database Criteria via Interactive Ranking

Tompkin, J., Kim, K. I., Pfister, H. & Theobalt, C. 2017 Proc. British Machine Vision Conference, 2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Unsupervised learning
Metadata
Labels
Geometry
Experiments

Predictor Combination at Test Time

Kim, K. I., Tompkin, J. & Richardt, C. 22 Oct 2017 Proceedings of the International Conference on Computer Vision (ICCV), 2017. IEEE, p. 3553-3561 9 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Learning algorithms