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Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking

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jchenluo/EDA_GNN

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Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking

A PyTorch implementation combines with Siamese Network and Graph Neural Network for Online Multiple-Object Tracking.

Dataset available at [https://motchallenge.net/]

According paper can be found at [https://arxiv.org/abs/1907.05315]

How to run

Use python main.py to train a model from scratch. Settings for training is in config.yml.
Use python tracking.py to track a test video, meanwhile you need to provide the detected objects & tracking results for the first five frames. Setting for tracking is in setting/.

Requirements

  • Python 2.7.12
  • numpy 1.11.0
  • scipy 1.1.0
  • torchvision 0.2.1
  • opencv_python 3.3.0.10
  • easydict 1.7
  • torch 0.4.1
  • Pillow 6.2.0
  • PyYAML 5.1

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Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking

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