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README.md

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 #### Note: This repository will be updated on a regular basis, so stay tuned~~🎉🎉🎉
 
 ## News: 
-**We recommend our newly-released repository [BasicLFSR](https://github.com/ZhengyuLiang24/BasicLFSR), which is an open-source and easy-to-use toolbox for LF image SR. Both this repo and [BasicLFSR](https://github.com/ZhengyuLiang24/BasicLFSR) are developed to make the communities better get access to this area and re-implement existing methods.**
-
-## Recent Updates:
+* **2022.12.18: We will organize the first LF image SR challenge on the NTIRE workshop at CVPR 2023. See details at [LF-Image-SR/tree/NTIRE2023](https://github.com/YingqianWang/LF-Image-SR/tree/NTIRE2023).**
 * **2022.06.14: Add a new work [YingqianWang/LF-DAnet](https://github.com/YingqianWang/LF-DAnet).**
 * **2022.02.17: Add a new work [YingqianWang/DistgSSR](https://github.com/YingqianWang/DistgSSR) that is accepted to [TPAMI](https://arxiv.org/pdf/2202.10603.pdf).**
 * **2022.01.23: Update [ZhengyuLiang24/LFT](https://github.com/ZhengyuLiang24/LFT) that is accepted by [IEEE SPL](https://arxiv.org/pdf/2108.07597.pdf).**
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 | **DistgSSR**     | Disentangling Light Fields for Super-Resolution and Disparity Estimation, [TPAMI 2022](https://arxiv.org/pdf/2202.10603.pdf). | [YingqianWang/DistgSSR](https://github.com/YingqianWang/DistgSSR) |
 | **LF-DAnet**     | Learning a Degradation-Adaptive Network for Light Field Image Super-Resolution, [arXiv 2022](https://arxiv.org/pdf/2206.06214.pdf). | [YingqianWang/LF-DAnet](https://github.com/YingqianWang/LF-DAnet) |
 
-## Acknowledgement
-**We would like to thank [Zhengyu Liang](https://github.com/ZhengyuLiang24) and [Zhen Cheng](https://github.com/Joechann0831) for the helpful discussions and insightful suggestions regarding this repository.**
-
-## Contact
-**Any question regarding this repo can be addressed to yingqian.wang@outlook.com.**
-