Update README.md

README.md

@@ -11,4 +11,34 @@ Please visit our github repository ([PyTorch-StudioGAN](https://github.com/POSTE
   <img width="95%" src="https://raw.githubusercontent.com/POSTECH-CVLab/PyTorch-StudioGAN/master/docs/figures/StudioGAN_Benchmark.png"/>
 </p>
 
-license: mit
+## License
+PyTorch-StudioGAN is an open-source library under the MIT license (MIT). However, portions of the library are avaiiable under distinct license terms: StyleGAN2, StyleGAN2-ADA, and StyleGAN3 are licensed under [NVIDIA source code license](https://github.com/POSTECH-CVLab/PyTorch-StudioGAN/blob/master/LICENSE-NVIDIA), and PyTorch-FID is licensed under [Apache License](https://github.com/POSTECH-CVLab/PyTorch-StudioGAN/blob/master/src/metrics/fid.py).
+
+## Citation
+StudioGAN is established for the following research projects. Please cite our work if you use StudioGAN.
+```bib
+@article{kang2022StudioGAN,
+  title   = {{StudioGAN: A Taxonomy and Benchmark of GANs for Image Synthesis}},
+  author  = {MinGuk Kang and Joonghyuk Shin and Jaesik Park},
+  journal = {2206.09479 (arXiv)},
+  year    = {2022}
+}
+```
+
+```bib
+@inproceedings{kang2021ReACGAN,
+  title   = {{Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training}},
+  author  = {Minguk Kang, Woohyeon Shim, Minsu Cho, and Jaesik Park},
+  journal = {Conference on Neural Information Processing Systems (NeurIPS)},
+  year    = {2021}
+}
+```
+
+```bib
+@inproceedings{kang2020ContraGAN,
+  title   = {{ContraGAN: Contrastive Learning for Conditional Image Generation}},
+  author  = {Minguk Kang and Jaesik Park},
+  journal = {Conference on Neural Information Processing Systems (NeurIPS)},
+  year    = {2020}
+}
+```