UFG-NCD

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(CVPR2024 Highlight) Novel Class Discovery for Ultra-Fine-Grained Visual Categorization (UFG-NCD)

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# UFG-NCD
Official pytorch implementation of our paper: [*Novel Class Discovery for Ultra-Fine-Grained Visual Categorization*](https://openaccess.thecvf.com/content/CVPR2024/papers/Liu_Novel_Class_Discovery_for_Ultra-Fine-Grained_Visual_Categorization_CVPR_2024_paper.pdf) (CVPR2024 **Highlight**)

![overview](https://raw.githubusercontent.com/SSDUT-Caiyq/UFG-NCD/main/assets/overview.jpg)

## Environment :snake:

Our implementation is based on [uno](https://github.com/DonkeyShot21/UNO), while logging is performed using `wandb`, we use `conda` to create the environment and install the dependencies.

Follow the commands below to setup environment.

```bash
# create environment
conda create -n rapl python=3.8
conda activate rapl

# choose the cudatoolkit version on your own
conda install pytorch==1.7.1 torchvision==0.8.2 cudatoolkit=11.0 -c pytorch

# install other dependencies
pip install tqdm wandb scikit-learn pandas pytorch-lightning==1.1.3 lightning-bolts==0.3.0

# create checkpoints directory
mkdir checkpoints
```

## Datasets :floppy_disk:

We use Ultra-FGVC as our main experiment datasets, specifically the `SoyAgeing-{R1, R3, R4, R5, R6}`.

You can download the datasets [here](https://github.com/XiaohanYu-GU/Ultra-FGVC), also make sure you have changed the datasets root that defined in [`config.py`](./config.py).

## Supervised Learning :star2:

```bash
python supervised_learning.py --dataset SoyAgeing-R1 --task ncd
```

## Discovery Learning :sparkles:

```bash
python discovery_learning.py --dataset SoyAgeing-R1 --task ncd --pretrained ncd-supervised-SoyAgeing-R1-pc2.0-cra0.6-reg1.0.pth
```

## Citation :clipboard:

If you find our work helpful, please consider citing our paper:

```tex
@InProceedings{Liu_2024_CVPR,
    author    = {Liu, Yu and Cai, Yaqi and Jia, Qi and Qiu, Binglin and Wang, Weimin and Pu, Nan},
    title     = {Novel Class Discovery for Ultra-Fine-Grained Visual Categorization},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2024},
    pages     = {17679-17688}
}
```

## Acknowledgements :gift:

- [UNO](https://github.com/DonkeyShot21/UNO)
- [Ultra-FGVC](https://github.com/XiaohanYu-GU/Ultra-FGVC)

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