Person Re-identification

Overview

Person Re-identification

Final project of Computer Vision

Table of content

Students:

Name Student ID Email
Nguyen Hoang Quan 18120145 [email protected]
Le Minh Khoa 18120415 [email protected]

Proposed method

Proposed method

Dataset

Dataset preparation

Download raw dataset

Download Market-1501 via Google Drive: link

Set dataset path

In config.json file, change root value to dataset path.

Train

Config

Check config.json file for training configuration.

Run

Run python main.py to start training.

Evaluation

Methods Train feature Test feature Rank-1 Rank-5 mAP
Baseline Global Global 83.28 94.18 65.96
Baseline Local Local 80.20 92.76 59.66
Baseline Global, Local Global 84.14 93.97 67.58
Baseline Global, Local Local 86.37 95.10 68.68
Baseline + Identity Loss Global, Local Global 83.55 93.35 67.66
Baseline + Identity Loss Global, Local Local 84.23 93.62 63.99
Baseline + Identity Loss + Random Flip Global, Local Global 85.42 93.97 69.34
Baseline + Identity Loss + Random Flip Global, Local Local 86.82 94.89 67.59
Re-ranking Global, Local Global 87.47 92.96 82.90
Re-ranking + Identity Loss Global, Local Global 86.19 92.76 81.27
Re-ranking + Identity loss + Random Flip Global, Local Global 87.50 92.93 82.68
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