SSC-TLR

The implementation of our paper Semi-Supervised Subspace Clustering via Tensor Low-Rank Representation https://arxiv.org/abs/2205.10481

This repository contains:

1. Datasets and Selected Annotations in our paper, includeing ORL, YaleB, COIL20, Isolet, MNIST, Alphabet, BF0502 and Notting-Hill.
2. A Function to implement the proposed method.
3. A Comparision Demo of the mentioned methods (you may need to refer to possible official implementations, or implement them yourself) in our manuscript, including LRR, DPLRR, SSLRR, L-RPCA, CP-SSC, SC-LRR and CLRR.
4. Some raw experimental Results.
5. A Visualization Demo of the result files.

Usage

Before running the code, you need to download the following toolboxes:

1. LibADMM library from: https://github.com/canyilu/LibADMM
2. Graph Signal Processing Toolbox (GSPBox) from: https://github.com/epfl-lts2/gspbox
3. Clustering Measure from: https://github.com/jyh-learning/MVSC-TLRR

Citation

If you find the code useful, please feel free to cite our paper:

@article{lu2022semi, title={Semi-Supervised Subspace Clustering via Tensor Low-Rank Representation}, author={Lu, Guanxing and Jia, Yuheng and Hou, Junhui}, journal={arXiv preprint arXiv:2205.10481}, year={2022} }

Contact

Any questions, please contact me through guanxing AT seu DOT edu DOT cn