Update README.md

README.md

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 The implementation of TNNLS 2020 paper ["3D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising"](https://arxiv.org/abs/2003.04547)
 
+> 🌟 See also the follow up works of QRNN3D:
+> - [DPHSIR](https://github.com/Zeqiang-Lai/DPHSIR) - Plug-and-play QRNN3D that solve any HSI restoration task in one model.
+> - [HSDT](https://github.com/Zeqiang-Lai/HSDT) - State-of-the-art HSI denoising transformer that follows up 3D paradigam of QRNN3D.
+> - [MAN](https://github.com/Zeqiang-Lai/MAN) - Improved QRNN3D with significant performance improvement and less parameters.
+>
+> 📉 Performance: QRNN3D < DPHSIR < MAN < HSDT
 
 ## Highlights
 
@@ -78,5 +84,31 @@ If you find this work useful for your research, please cite:
 }
 ```
 
+and follow up works
+```bibtex
+@article{lai2022dphsir,
+ title = {Deep plug-and-play prior for hyperspectral image restoration},
+ journal = {Neurocomputing},
+ volume = {481},
+ pages = {281-293},
+ year = {2022},
+ issn = {0925-2312},
+ doi = {https://doi.org/10.1016/j.neucom.2022.01.057},
+ author = {Zeqiang Lai and Kaixuan Wei and Ying Fu},
+}
+@inproceedings{lai2023hsdt,
+ author = {Lai, Zeqiang and Chenggang, Yan and Fu, Ying},
+ title = {Hybrid Spectral Denoising Transformer with Guided Attention},
+ booktitle={Proceedings of the IEEE International Conference on Computer Vision},
+ year = {2023},
+}
+@article{lai2023mixed,
+ title={Mixed Attention Network for Hyperspectral Image Denoising},
+ author={Lai, Zeqiang and Fu, Ying},
+ journal={arXiv preprint arXiv:2301.11525},
+ year={2023}
+}
+```
+
 ## Contact
 Please contact me if there is any question ([email protected] ~~[email protected]~~)