From 8bc217c9748da00b332deeba14957d56d9562f10 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Junhao=20Zhuang=20=28=E5=BA=84=E4=BF=8A=E8=B1=AA=29?=
 <108931120+zhuang2002@users.noreply.github.com>
Date: Mon, 15 Dec 2025 12:27:50 +0800
Subject: [PATCH] Add community projects related to Wan2.1

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 8f03f2a..8b37449 100644
--- a/README.md
+++ b/README.md
@@ -36,6 +36,7 @@ In this repository, we present **Wan2.1**, a comprehensive and open suite of vid
 
 ## Community Works
 If your work has improved **Wan2.1** and you would like more people to see it, please inform us.
+- [FlashVSR](https://github.com/OpenImagingLab/FlashVSR), a real-time one-step diffusion-based streaming video super-resolution framework based on **Wan2.1-T2V-1.3B** for high-resolution, high-quality video super-resolution. Refer to the [project page](https://zhuang2002.github.io/FlashVSR) for more examples.
 - [DriVerse](https://github.com/shalfun/DriVerse), an autonomous driving world model based on **Wan2.1-14B-I2V**, generates future driving videos conditioned on any scene frame and given trajectory. Refer to the [project page](https://github.com/shalfun/DriVerse/tree/main) for more examples.
 - [Training-Free-WAN-Editing](https://github.com/KyujinHan/Awesome-Training-Free-WAN2.1-Editing), built on **Wan2.1-T2V-1.3B**, allows training-free video editing with image-based training-free methods, such as [FlowEdit](https://arxiv.org/abs/2412.08629) and [FlowAlign](https://arxiv.org/abs/2505.23145).
 - [Wan-Move](https://github.com/ali-vilab/Wan-Move), accepted to NeurIPS 2025, a framework that brings **Wan2.1-I2V-14B** to SOTA fine-grained, point-level motion control! Refer to [their project page](https://wan-move.github.io/) for more information.