Update README.md

README.md

@@ -119,41 +119,18 @@ The fine-tuning instruction is in [FINETUNE.md](FINETUNE.md).
 
 ## ⚠️ Our code is based on [VideoMAE](https://github.com/MCG-NJU/VideoMAE) code base. 
 
-<!-- We provide pre-trained and fine-tuned models in [MODEL_ZOO.md](MODEL_ZOO.md). -->
-
-<!-- ## 👀 Visualization -->
-
-<!-- We provide the script for visualization in [`vis.sh`](vis.sh).  Colab notebook for better visualization is coming soon. -->
-
-<!-- ## ☎️ Contact 
-
-Zhan Tong: [email protected]
-
-## 👍 Acknowledgements
-
-Thanks to [Ziteng Gao](https://sebgao.github.io/), Lei Chen, [Chongjian Ge](https://chongjiange.github.io/), and [Zhiyu Zhao](https://github.com/JerryFlymi) for their kind support.<br>
-This project is built upon [MAE-pytorch](https://github.com/pengzhiliang/MAE-pytorch) and [BEiT](https://github.com/microsoft/unilm/tree/master/beit). Thanks to the contributors of these great codebases.
-
-## 🔒 License
-
-The majority of this project is released under the CC-BY-NC 4.0 license as found in the [LICENSE](https://github.com/MCG-NJU/VideoMAE/blob/main/LICENSE) file. Portions of the project are available under separate license terms: [SlowFast](https://github.com/facebookresearch/SlowFast) and [pytorch-image-models](https://github.com/rwightman/pytorch-image-models) are licensed under the Apache 2.0 license. [BEiT](https://github.com/microsoft/unilm/tree/master/beit) is licensed under the MIT license.
-
 ## ✏️ Citation
 
 If you think this project is helpful, please feel free to leave a star⭐️ and cite our paper:
 
 ```
-@inproceedings{tong2022videomae,
-  title={Video{MAE}: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training},
-  author={Zhan Tong and Yibing Song and Jue Wang and Limin Wang},
-  booktitle={Advances in Neural Information Processing Systems},
-  year={2022}
-}
 
-@article{videomae,
-  title={VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training},
-  author={Tong, Zhan and Song, Yibing and Wang, Jue and Wang, Limin},
-  journal={arXiv preprint arXiv:2203.12602},
-  year={2022}
+@article{salehi2024sigma,
+  title={SIGMA: Sinkhorn-Guided Masked Video Modeling},
+  author={Salehi, Mohammadreza and Dorkenwald, Michael and Thoker, Fida Mohammad and Gavves, Efstratios and Snoek, Cees GM and Asano, Yuki M},
+  journal={European Conference of Computer Vision},
+  year={2024}
 }
+
+```
 ``` -->