docs: update readme with table of attacks

README.md

@@ -1,7 +1,41 @@
-# torchattack [![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v1.json)](https://github.com/charliermarsh/ruff) [![pdm-managed](https://img.shields.io/badge/pdm-managed-blueviolet)](https://pdm.fming.dev)
+# 🛡 torchattack
 
-A set of adversarial attacks implemented in PyTorch. _For use internally._
+[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v1.json)](https://github.com/charliermarsh/ruff)
+[![pdm-managed](https://img.shields.io/badge/pdm-managed-blueviolet)](https://pdm.fming.dev)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+
+A set of adversarial attacks implemented in PyTorch. _For internal use._
 
 ```shell
 pip install git+https://github.com/daisylab-bit/torchattack
 ```
+
+## Usage
+
+```python
+from torchattack import FGSM, MIFGSM
+
+# Initialize an attack
+attack = FGSM(model, eps=0.03)
+
+# Initialize an attack with extra params
+attack = MIFGSM(model, eps=0.03, steps=10, decay=1.0)
+```
+
+## Attacks
+
+| Name       | Paper                                                                                                                      | `torchattack` class    |
+| ---------- | -------------------------------------------------------------------------------------------------------------------------- | ---------------------- |
+| FGSM       | [Explaining and Harnessing Adversarial Examples](https://arxiv.org/abs/1412.6572)                                          | `torchattack.FGSM`     |
+| PGD        | [Towards Deep Learning Models Resistant to Adversarial Attacks](https://arxiv.org/abs/1706.06083)                          | `torchattack.PGD`      |
+| MI-FGSM    | [Boosting Adversarial Attacks with Momentum](https://arxiv.org/abs/1710.06081)                                             | `torchattack.MIFGSM`   |
+| DI-FGSM    | [Improving Transferability of Adversarial Examples with Input Diversity](https://arxiv.org/abs/1803.06978)                 | `torchattack.DIFGSM`   |
+| TI-FGSM    | [Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks](https://arxiv.org/abs/1904.02884) | `torchattack.TIFGSM`   |
+| NI-FGSM    | [Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks](https://arxiv.org/abs/1908.06281)             | `torchattack.NIFGSM`   |
+| SI-NI-FGSM | [Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks](https://arxiv.org/abs/1908.06281)             | `torchattack.SINIFGSM` |
+| VMI-FGSM   | [Enhancing the Transferability of Adversarial Attacks through Variance Tuning](https://arxiv.org/abs/2103.15571)           | `torchattack.VMIFGSM`  |
+| VNI-FGSM   | [Enhancing the Transferability of Adversarial Attacks through Variance Tuning](https://arxiv.org/abs/2103.15571)           | `torchattack.VNIFGSM`  |
+
+## License
+
+[MIT](LICENSE)