# TransZero

**Repository Path**: indecisive_c/TransZero

## Basic Information

- **Project Name**: TransZero
- **Description**: No description available
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: test
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-11-03
- **Last Updated**: 2023-11-03

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# TransZero [[arXiv]](https://arxiv.org/pdf/2112.01683.pdf)


This repository contains the testing code for the paper  "***TransZero: Attribute-guided Transformer for Zero-Shot Learning***" accepted to AAAI 2022. We have released the training codes of this work in [train branch](https://github.com/shiming-chen/TransZero).

![](figs/pipeline.png)


## Preparing Dataset and Model

We provide trained models ([Google Drive](https://drive.google.com/drive/folders/1WK9pm2eX2Rl4rWqXqe_EZiAM8wWB8yqG?usp=sharing)) on three different datasets: [CUB](http://www.vision.caltech.edu/visipedia/CUB-200-2011.html), [SUN](http://cs.brown.edu/~gmpatter/sunattributes.html), [AWA2](http://cvml.ist.ac.at/AwA2/) in the CZSL/GZSL setting. You can download model files as well as corresponding datasets, and organize them as follows: 
```
.
├── saved_model
│   ├── TransZero_CUB_CZSL.pth
│   ├── TransZero_CUB_GZSL.pth
│   ├── TransZero_SUN_CZSL.pth
│   ├── TransZero_SUN_GZSL.pth
│   ├── TransZero_AWA2_CZSL.pth
│   └── TransZero_AWA2_GZSL.pth
├── data
│   ├── CUB/
│   ├── SUN/
│   └── AWA2/
└── ···
```

## Requirements
The code implementation of **TransZero** mainly based on [PyTorch](https://pytorch.org/). All of our experiments run and test in Python 3.8.8. To install all required dependencies:
```
$ pip install -r requirements.txt
```
## Runing
Runing following commands and testing **TransZero** on different dataset:

CUB Dataset: 
```
$ python test.py --config config/CUB_CZSL.json      # CZSL Setting
$ python test.py --config config/CUB_GZSL.json      # GZSL Setting
```
SUN Dataset:
```
$ python test.py --config config/SUN_CZSL.json      # CZSL Setting
$ python test.py --config config/SUN_GZSL.json      # GZSL Setting
```
AWA2 Dataset: 
```
$ python test.py --config config/AWA2_CZSL.json     # CZSL Setting
$ python test.py --config config/AWA2_GZSL.json     # GZSL Setting
```

## Results
Results of our released models using various evaluation protocols on three datasets, both in the conventional ZSL (CZSL) and generalized ZSL (GZSL) settings.

| Dataset | Acc(CZSL) | U(GZSL) | S(GZSL) | H(GZSL) |
| :-----: | :-----: | :-----: | :-----: | :-----: |
| CUB | 76.8 | 69.3 | 68.3 | 68.8 |
| SUN | 65.6 | 52.6 | 33.4 | 40.8 |
| AWA2 | 70.1 | 61.3 | 82.3 | 70.2 |

**Note**: All of above results are run on a server with an AMD Ryzen 7 5800X CPU and a NVIDIA RTX A6000 GPU.

## Citation
If this work is helpful for you, please cite our paper.

```
@InProceedings{Chen2021TransZero,
    author    = {Chen, Shiming and Hong, Ziming and Liu, Yang and Xie, Guo-Sen and Sun, Baigui and Li, Hao and Peng, Qinmu and Lu, Ke and You, Xinge},
    title     = {TransZero: Attribute-guided Transformer for Zero-Shot Learning},
    booktitle = {Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI)},
    year      = {2022}
}
```

## References
Parts of our codes based on:
* [hbdat/cvpr20_DAZLE](https://github.com/hbdat/cvpr20_DAZLE)
* [zhangxuying1004/RSTNet](https://github.com/zhangxuying1004/RSTNet)

## Contact
If you have any questions about codes, please don't hesitate to contact us by gchenshiming@gmail.com or hoongzm@gmail.com.