deep-person-reid

This repo contains pytorch implementations of deep person re-identification approaches.

We will actively maintain this repo.

Pretrained models

Prepare data

Train

Test

Results

Setup

• Image size: 256-by-128
  
• Optimizer: Adam [6]
  
• Loss functions:
  xent: cross entropy + label smoothing regularizer [5]
  htri: triplet loss with hard positive/negative mining [4]
  

Market1501

Model	Size (M)	Loss	Rank-1 / -5 / -10 (%)	mAP (%)	Reported Rank	Reported mAP
ResNet50 [1]	25.05	xent	85.8 / 94.4 / 96.3	70.1
ResNet50M [2]	30.01	xent	88.8 / 95.3 / 97.0	74.4	89.9 / - / -	75.6
DenseNet121 [3]	7.72	xent

References

[1] He et al. Deep Residual Learning for Image Recognition. CVPR 2016.
[2] Yu et al. The Devil is in the Middle: Exploiting Mid-level Representations for Cross-Domain Instance Matching. arXiv:1711.08106.
[3] Huang et al. Densely Connected Convolutional Networks. CVPR 2017.
[4] Hermans et al. In Defense of the Triplet Loss for Person Re-Identification. arXiv:1703.07737.
[5] Szegedy et al. Rethinking the Inception Architecture for Computer Vision. CVPR 2016.
[6] Kingma and Ba. Adam: A Method for Stochastic Optimization. ICLR 2015.