/MGN-pytorch

Reproduction of paper: Learning Discriminative Features with Multiple Granularities for Person Re-Identification

Primary LanguagePython

Multiple Granularity Network

Reproduction of paper:Learning Discriminative Features with Multiple Granularities for Person Re-Identification

Dependencies

  • Python >= 3.5
  • PyTorch >= 0.4.0
  • TorchVision
  • Matplotlib
  • Argparse
  • Sklearn
  • Pillow
  • Numpy
  • Scipy
  • Tqdm

Train

Prepare training data

Download Market1501 training data.here

Begin to train

In the demo.sh file, add the Market1501 directory to --datadir

run sh demo.sh

Result

mAP rank1 rank3 rank5 rank10
2018-7-22 92.17 94.60 96.53 97.06 98.01
2018-7-24 93.53 95.34 97.06 97.68 98.49
last 93.83 95.78 97.21 97.83 98.43

Download model file in here

The architecture of Multiple Granularity Network (MGN)

Multiple Granularity Network

Figure . Multiple Granularity Network architecture.

@ARTICLE{2018arXiv180401438W,
    author = {{Wang}, G. and {Yuan}, Y. and {Chen}, X. and {Li}, J. and {Zhou}, X.},
    title = "{Learning Discriminative Features with Multiple Granularities for Person Re-Identification}",
    journal = {ArXiv e-prints},
    archivePrefix = "arXiv",
    eprint = {1804.01438},
    primaryClass = "cs.CV",
    keywords = {Computer Science - Computer Vision and Pattern Recognition},
    year = 2018,
    month = apr,
    adsurl = {http://adsabs.harvard.edu/abs/2018arXiv180401438W},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}