Pytorch Implementation of Deep Orthogonal Fusion of Local and Global Features (DOLG)

This is the unofficial PyTorch Implementation of "DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features"

reference: https://arxiv.org/pdf/2108.02927.pdf

Prerequisites

• PyTorch
• PyTorch Lightning
• timm
• sklearn
• pandas
• jpeg4py
• albumentations
• python3
• CUDA

Data

You can get the GLDv2 dataset from here.

If you just want the GLDv2-clean dataset, check this kaggle competition dataset.

Place your data like the structure below

data
├── train_clean.csv
└── train
    └── ###
        └── ###
            └── ###
                └── ###.jpg

Citations

@misc{yang2021dolg,
      title={DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features}, 
      author={Min Yang and Dongliang He and Miao Fan and Baorong Shi and Xuetong Xue and Fu Li and Errui Ding and Jizhou Huang},
      year={2021},
      eprint={2108.02927},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}