Awesome
Combination of Multiple Global Descriptors for Image Retrieval
This is the repository to reproduce the results of our paper "Combination of Multiple Global Descriptors for Image Retrieval".
HeeJae Jun*, Byungsoo Ko*, Youngjoon Kim, Insik Kim, Jongtack Kim (* Authors contributed equally.)
@NAVER/LINE Vision
Approach
<div align="center"> <img src="figures/architecture.png"> </div>Prerequisite
- Python 2.7 or above
- MXNet-1.4.0 or above
- Numpy and tqdm
Usage
Download dataset
$ bash download.sh cub200
Extract pre-trained model
$ tar zxvf ./checkpoints/CGD.CUB200.C_concat_MG.ResNet50v.dim1536.tar.gz -C ./checkpoints/
Test
$ python test.py
usage: test.py [-h] [--image-width IMAGE_WIDTH] [--image-height IMAGE_HEIGHT]
[--batch-size BATCH_SIZE] [--num-workers NUM_WORKERS]
[--recallk RECALLK] [--data-dir DATA_DIR]
[--train-txt TRAIN_TXT] [--test-txt TEST_TXT]
[--bbox-txt BBOX_TXT] --pretrained-model PRETRAINED_MODEL
[--gpu GPU]
$ python test.py --pretrained-model=checkpoints/CGD.CUB200.C_concat_MG.ResNet50v.dim1536
...
R@ 1: 0.7681
R@ 2: 0.8484
R@ 4: 0.9060
R@ 8: 0.9433
Citation
@article{jun2019combination,
title={Combination of Multiple Global Descriptors for Image Retrieval},
author={Jun, HeeJae and Ko, ByungSoo and Kim, Youngjoon and Kim, Insik and Kim, Jongtack},
journal={arXiv preprint arXiv:1903.10663},
year={2019}
}
License
Copyright 2019-present NAVER Corp.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.