ZHUO, Shaojie 卓少杰
School of Computing
National University of Singapore
Computing 1, 13 Computing Drive
Singapore 117417
Email:
I am a Ph.D student in the Computer Vision Lab of Computer Science Department, School of Computing, National University of Singapore. My supervisor is Assisstant Prof. Terence Sim. My research interests are in the areas of Computer Vision, Image Processing, Computer Graphics. In particular, I worked on Computational focus manipulation, Computational low light photography and old document processing.

Education

2005.7 - present, Ph.D Candidate, School of Computing, National University of Singapore
2001.9 - 2005.6, B.S., School of Computer Science, Fudan University, China

Projects

Semantic Colorization with Internet Images
Yong Sang Chia, Shaojie Zhuo, Raj Kumar Gupta, Yu-Wing Tai, Siu-Yeung Cho, Ping Tan, Stephen Lin
ACM Transaction on Graphics(TOG) and Proc. of SIGGRAPH Asia 2011.
PDF

Enhancing Low Light Images Using Near Infrared Flash Images
Shaojie Zhuo, Xiaopeng Zhang, Xiaoping Miao and Terence Sim
IEEE Conference on Image Processing (ICIP), 2010
High-res PDF (12.1M) | Low-res PDF (1.7M) |

Interactive Visualization of Hyperspectral Images of Historical Documents
Seon Joo Kim, Shaojie Zhuo, Fanbo Deng, Chi-Wing Fu and Michael S. Brown
IEEE Transactions on Visualization and Computer Graphics (TVCG) (Proc. of IEEE Visualization Conference), volume 16, number 6, pages 1441-1448, 2010.

Robust Flash Deblurring
Shaojie Zhuo, Dong Guo and Terence Sim
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010
High-res PDF (36.8M) | Low-res PDF (7.6M) | Image Data

Correcting Over-Exposure in Photographs
Dong Guo, Yuan Cheng, Shaojie Zhuo and Terence Sim
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010
PDF (3.9M)

Defocus Map Estimation from a Single Image
Shaojie Zhuo and Terence Sim
Pattern Recognition, volume 44, number 9, pages 1852-1858, 2011
PDF (7.3M) | Image Data

On the Recovery of Depth from a Single Defocus Image
Shaojie Zhuo and Terence Sim
International Conference on Computer Analysis of Images and Patterns (CAIP), 2009 (Oral)
PDF (1.4M)

Example-based Sparsity Prior for Image Deconvolution
We propose an example-based sparsity prior for image deconvolution which can significantly suppress the noise and ringing effects, while preserving details of the original image.