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README.md

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 Both methods can be used for synthetic and real-world dataset. You can find more details and results from this **[Project page](https://algolzw.github.io/ir-sde/index.html)**.
 
 ### Updates
-[**2023.04.23**] We released all codes (*IR-SDE* and *Refusion*) for various tasks as well as the U-Net based *Latent-Refusion* model.<br>
+[**2023.04.23**] We released the codes for various tasks (including *IR-SDE* and *Refusion*), and also released the U-Net based **Latent-Refusion** code.<br>
 [**2023.04.17**] 🎉🎉🎉 Our method **Refusion** won the 2nd place in NTIRE 2023 Image Shadow Removal Challenge [[Paper]](https://arxiv.org/abs/2304.08291).<br>
 <!--[**2023.02.02**] We provide a [Gradio](https://gradio.app/) app file for the case that you want to [test your own images](https://github.com/Algolzw/image-restoration-sde#Gradio).-->