Unofficial PyTorch Implementation of "DOLG: Single-Stage Image Retrieval with Deep Orthogonal Fusion of Local and Global Features"

Overview

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}
}
Owner
DK
Computer Science/Artificial Intelligence Major at Carnegie Mellon University
DK
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