no code implementations • 31 Jan 2023 • Lan Tang, Xiaxi Li, Jinyuan Zhang, Guiying Li, Peng Yang, Ke Tang
The training process is accelerated up to 7x on tested games, comparing to its counterpart without the surrogate and PE.
no code implementations • 22 Mar 2018 • Zhiyuan Zha, Xinggan Zhang, Qiong Wang, Yechao Bai, Lan Tang, Xin Yuan
Inspired by group-based sparse coding, recently proposed group sparsity residual (GSR) scheme has demonstrated superior performance in image processing.
no code implementations • 24 Apr 2017 • Zhiyuan Zha, Xinggan Zhang, Yu Wu, Qiong Wang, Lan Tang
Since the matrix formed by nonlocal similar patches in a natural image is of low rank, the nuclear norm minimization (NNM) has been widely used in various image processing studies.
no code implementations • 24 Apr 2017 • Zhiyuan Zha, Xinggan Zhang, Qiong Wang, Lan Tang, Xin Liu
In this paper, a group-based sparse representation method with non-convex regularization (GSR-NCR) for image CS reconstruction is proposed.
no code implementations • 5 Apr 2017 • Qiong Wang, Xinggan Zhang, Yu Wu, Lan Tang, Zhiyuan Zha
Nonlocal image representation or group sparsity has attracted considerable interest in various low-level vision tasks and has led to several state-of-the-art image denoising techniques, such as BM3D, LSSC.
no code implementations • 1 Mar 2017 • Zhiyuan Zha, Xinggan Zhang, Qiong Wang, Lan Tang, Xin Liu
Unlike the conventional group-based sparse representation denoising methods, two kinds of prior, namely, the NSS priors of noisy and pre-filtered images, are used in GSRC.
no code implementations • 15 Feb 2017 • Zhiyuan Zha, Xin Yuan, Bei Li, Xinggan Zhang, Xin Liu, Lan Tang, Ying-Chang Liang
However, it still lacks a sound mathematical explanation on why WNNM is more feasible than NNM.
no code implementations • 3 Jan 2017 • Zhiyuan Zha, Xinggan Zhang, Qiong Wang, Yechao Bai, Lan Tang
To boost the performance of image denoising, the concept of group sparsity residual is proposed, and thus the problem of image denoising is transformed into one that reduces the group sparsity residual.
no code implementations • 28 Nov 2016 • Zhiyuan Zha, Xin Liu, Xiaohua Huang, Henglin Shi, Yingyue Xu, Qiong Wang, Lan Tang, Xinggan Zhang
Then, we prove that group-based sparse coding is equivalent to the rank minimization problem, and thus the sparse coefficient of each group is measured by estimating the singular values of each group.
no code implementations • 12 Sep 2016 • Zhiyuan Zha, Xin Liu, Ziheng Zhou, Xiaohua Huang, Jingang Shi, Zhenhong Shang, Lan Tang, Yechao Bai, Qiong Wang, Xinggan Zhang
Group sparsity has shown great potential in various low-level vision tasks (e. g, image denoising, deblurring and inpainting).