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Zhou Liu

4 papers hereh-index 10360 citations24 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.IV2
  • cs.CV1
  • cs.LG1
same name
  • Zhou Liu — 1 paper
  • Zhou Liu — 1 paper
  • Zhou Liu — 1 paper
  • Zhou Liu — 1 paper
  • Zhou Liu — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182020
most citedImage Super-Resolution via RL-CSC: When Residual Learning Meets Convolutional Sparse Coding

5 citations · 6 across the 3 of their papers we have counts for

collaborators

4 papers

eess.IV2020

Mixed Noise Removal with Pareto Prior

Zhou Liu, Lei Yu, Gui-Song Xia +1

Denoising images contaminated by the mixture of additive white Gaussian noise (AWGN) and impulse noise (IN) is an essential but challenging problem. The presence of impulsive distu…

cs.LG2019★ 1 cited

Learning Cluster Structured Sparsity by Reweighting

Yulun Jiang, Lei Yu, Haijian Zhang +1

Recently, the paradigm of unfolding iterative algorithms into finite-length feed-forward neural networks has achieved a great success in the area of sparse recovery. Benefit from a…

eess.IV2019

CRNet: Image Super-Resolution Using A Convolutional Sparse Coding Inspired Network

Menglei Zhang, Zhou Liu, Lei Yu

Convolutional Sparse Coding (CSC) has been attracting more and more attention in recent years, for making full use of image global correlation to improve performance on various com…

cs.CV2018★ 5 cited

Image Super-Resolution via RL-CSC: When Residual Learning Meets Convolutional Sparse Coding

Menglei Zhang, Zhou Liu, Lei Yu

We propose a simple yet effective model for Single Image Super-Resolution (SISR), by combining the merits of Residual Learning and Convolutional Sparse Coding (RL-CSC). Our model i…

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