English

A Benchmark for Sparse Coding: When Group Sparsity Meets Rank Minimization

Computer Vision and Pattern Recognition 2020-02-06 v5

Abstract

Sparse coding has achieved a great success in various image processing tasks. However, a benchmark to measure the sparsity of image patch/group is missing since sparse coding is essentially an NP-hard problem. This work attempts to fill the gap from the perspective of rank minimization. More details please see the manuscript....

Keywords

Cite

@article{arxiv.1709.03979,
  title  = {A Benchmark for Sparse Coding: When Group Sparsity Meets Rank Minimization},
  author = {Zhiyuan Zha and Xin Yuan and Bihan Wen and Jiantao Zhou and Jiachao Zhang and Ce Zhu},
  journal= {arXiv preprint arXiv:1709.03979},
  year   = {2020}
}

Comments

arXiv admin note: text overlap with arXiv:1611.08983

R2 v1 2026-06-22T21:40:48.301Z