lzrobots / NullSpace_ReID

Demo code for CVPR 2016 paper: Learning a Discriminative Null Space for Person Re-identification

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Discriminative Null Space for Person Re-ID

Demo code for CVPR 2016 paper: Learning a Discriminative Null Space for Person Re-identification

Li Zhang

Data

Download data from here and unzip it unzip data.zip.

It contains the LOMO feature [1] and kCCA feature [2] for VIPeR dataset.

Run

run demo.m in Matlab.

Results

We used the VIPeR data split provided by [2] in https://github.com/glisanti/KCCAReId.

For LOMO feature, we can get reported result 42.28% on VIPeR. (RBF kernel).

For kCCA feature, we can get 46.68% (CHI2 kernel), 45.92% (RBF kernel).

We can get reported score-level fusion result 51% on VIPeR.

CMC curve

Download the CMC curve on VIPeR, PRID, CUHK01, CUHK03 and Market1501 from here.

Citing

If you use this code in your research, please use the following BibTeX entry.

@inproceedings{zhang2016learning,
  title={Learning a discriminative null space for person re-identification},
  author={Zhang, Li and Xiang, Tao and Gong, Shaogang},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  year={2016}
}

References

ezoic increase your site revenue

About

Demo code for CVPR 2016 paper: Learning a Discriminative Null Space for Person Re-identification


Languages

Language:MATLAB 100.0%