no code implementations • 15 Nov 2016 • Hang Zhang, Fengyuan Zhu, Shixin Li
However, in real-world applications, it is common to see the training data contaminated by noises, which can affect the robustness of these matrix regression methods.
no code implementations • CVPR 2016 • Fengyuan Zhu, Guangyong Chen, Pheng-Ann Heng
This paper addresses this problem and proposes a novel blind image denoising algorithm which can cope with real-world noisy images even when the noise model is not provided.
no code implementations • 13 Jan 2016 • Guangyong Chen, Fengyuan Zhu, Pheng Ann Heng
We further develop a novel online learning approach for Variational inference and use it for the online learning of HeMF, which can efficiently cope with the important large-scale DDP problem.
no code implementations • 13 Jan 2016 • Fengyuan Zhu, Guangyong Chen, Jianye Hao, Pheng-Ann Heng
This paper addresses this problem and proposes a novel blind image denoising algorithm to recover the clean image from noisy one with the unknown noise model.
no code implementations • ICCV 2015 • Guangyong Chen, Fengyuan Zhu, Pheng Ann Heng
In this paper, we address the problem of estimating noise level from a single image contaminated by additive zero-mean Gaussian noise.