From 990af50de458c19590c245151197326e208d7191 Mon Sep 17 00:00:00 2001
From: Shiwei Zhang <134917139+Steven-SWZhang@users.noreply.github.com>
Date: Sun, 12 Oct 2025 11:07:45 +0800
Subject: [PATCH] Update README.md

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 README.md | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index ee26c94..aacd8a7 100644
--- a/README.md
+++ b/README.md
@@ -46,10 +46,12 @@ We are excited to introduce **Wan2.2**, a major upgrade to our foundational vide
 ## Community Works
 If your research or project builds upon [**Wan2.1**](https://github.com/Wan-Video/Wan2.1) or [**Wan2.2**](https://github.com/Wan-Video/Wan2.2), and you would like more people to see it, please inform us.
 
-- [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) provides comprehensive support for Wan 2.2, including low-GPU-memory layer-by-layer offload, FP8 quantization, sequence parallelism, LoRA training, full training.
-- [Kijai's ComfyUI WanVideoWrapper](https://github.com/kijai/ComfyUI-WanVideoWrapper) is an alternative implementation of Wan models for ComfyUI. Thanks to its Wan-only focus, it's on the frontline of getting cutting edge optimizations and hot research features, which are often hard to integrate into ComfyUI quickly due to its more rigid structure.
-- [Cache-dit](https://github.com/vipshop/cache-dit) offers Fully Cache Acceleration support for Wan2.2 MoE with DBCache, TaylorSeer and Cache CFG. Visit their [example](https://github.com/vipshop/cache-dit/blob/main/examples/pipeline/run_wan_2.2.py) for more details.
-- [FastVideo](https://github.com/hao-ai-lab/FastVideo) includes distilled Wan models with sparse attention that significanly speed up the inference time. 
+- [HuMo](https://github.com/Phantom-video/HuMo) proposed a unified, human-centric framework based on **Wan** to produce high-quality, fine-grained, and controllable human videos from multimodal inputs—including text, images, and audio. Visit their [webpage](https://phantom-video.github.io/HuMo/) for more details.
+- [FastVideo](https://github.com/hao-ai-lab/FastVideo) includes distilled **Wan** models with sparse attention that significanly speed up the inference time. 
+- [Cache-dit](https://github.com/vipshop/cache-dit) offers Fully Cache Acceleration support for **Wan2.2** MoE with DBCache, TaylorSeer and Cache CFG. Visit their [example](https://github.com/vipshop/cache-dit/blob/main/examples/pipeline/run_wan_2.2.py) for more details.
+- [Kijai's ComfyUI WanVideoWrapper](https://github.com/kijai/ComfyUI-WanVideoWrapper) is an alternative implementation of **Wan** models for ComfyUI. Thanks to its Wan-only focus, it's on the frontline of getting cutting edge optimizations and hot research features, which are often hard to integrate into ComfyUI quickly due to its more rigid structure.
+- [DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio) provides comprehensive support for **Wan 2.2**, including low-GPU-memory layer-by-layer offload, FP8 quantization, sequence parallelism, LoRA training, full training.
+
 
 ## 📑 Todo List
 - Wan2.2 Text-to-Video