BMVC20 - Deep Metric Learning Meets DeepClustering: An Novel Unsupervised Approach for Feature Embedding

AIOZ - BMVC 2020: "Deep Metric Learning Meets DeepClustering: An Novel UnsupervisedApproach for Feature Embedding"

This repository is the implementation of CBSwR for Unsupervised Deep Metric Learning task. Our model achieved 55.9, 37.6 on NMI, and 47.5, 45.6 on R@1 over CUB200-2001 and Car196 datasets, respectively. For the detail, please refer to link.

Summary

• The proposed framework
• Prerequisites
• Preprocessing
• Training
• Testing
• Citation
• License
• More information

The proposed framework

Prerequisites

Python3

Please install dependence package by run following command:

pip install -r requirements.txt

Preprocessing

CUB200-2011

The CUB200-2011 dataset should be downloaded via link. The downloaded file should be extracted to data/cub200 directory.

To pre-process CUB200-2011 dataset, please follow:

$ python pre_process/pre_process_cub200.py

Car196

The Car196 dataset should be downloaded via img_link and ano_link. The downloaded files should be extracted to data/car196 directory.

To pre-process Car196 dataset, please follow:

$ python pre_process/pre_process_car196.py

Training

To train CBSwR model on CUB200-2011 dataset, please follow:

$ python train.py --dataset cub200 --model_name CBSwR_CUB200

To train CBSwR model on Car196 dataset, please follow:

$ python train.py --dataset car196 --model_name CBSwR_Car196

The training scores will be printed every epoch.

Testing

In this repo, we include the pre-trained weight of CBSwR_CUB200 and CBSwR_Car196 models.

For CBSwR_CUB200 pretrained model. Please download the link and move to new_checkpoint. The trained CBSwR_CUB200 model can be tested in CUB200 validation set via:

$ python test.py --dataset cub200 --checkpoint_path new_checkpoint/CBSwR_CUB200.pth

For CBSwR_Car196 pretrained model. Please download the link and move to new_checkpoint. The trained CBSwR_Car196 model can be tested in Car196 validation set via:

$ python test.py --dataset car196 --checkpoint_path new_checkpoint/CBSwR_Car196.pth

Citation

If you use this code as part of any published research, we'd really appreciate it if you could cite the following paper:

@inproceedings{aioz_cbswr_bmvc2020,
  author    = {Nguyen, Binh X and Nguyen, Binh D and Carneiro, Gustavo and Tjiputra, Erman and Tran, Quang D and Do, Thanh-Toan},
  title     = {Deep Metric Learning Meets Deep Clustering: An Novel Unsupervised Approach for Feature Embedding},
  booktitle = {BMVC},
  year      = {2020}}
}

License

MIT License

More information

AIOZ AI Homepage: https://ai.aioz.io

AIOZ Network: https://aioz.network