From 77ace8024e8e97b488700635be6d7a215c69224c Mon Sep 17 00:00:00 2001 From: WayneJin0918 Date: Sun, 16 Aug 2026 09:09:35 +0800 Subject: [PATCH] Add Echo-Memory to Community Works. --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 3aa29f54..2dc0650b 100644 --- a/README.md +++ b/README.md @@ -47,6 +47,7 @@ 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. +- [Echo-Memory](https://github.com/Echo-Team-Joy-Future-Academy-JD/Echo-Memory), a controlled study of memory in action-conditioned video world models based on **Wan2.1-T2V-1.3B**. It holds the Wan backbone fixed and compares Context, Compression, Spatial, and State-Space memory when the camera leaves and later returns. Refer to the [project page](https://echo-team-joy-future-academy-jd.github.io/Echo-Memory/) and the [ZeroGPU demo](https://huggingface.co/spaces/hugging-apps/echo-memory) for more details. - [Prompt Relay](https://github.com/GordonChen19/Prompt-Relay), a plug-and-play, inference-time method for temporal control in video generation. Prompt Relay improves video quality and gives users precise control over what happens at each moment in the video. Visit their [webpage](https://gordonchen19.github.io/Prompt-Relay/) for more details. - [Helios](https://github.com/PKU-YuanGroup/Helios), a breakthrough video generation model base on **Wan2.1** that achieves minute-scale, high-quality video synthesis at 19.5 FPS on a single H100 GPU (about 10 FPS on a single Ascend NPU) —without relying on conventional long video anti-drifting strategies or standard video acceleration techniques. Visit their [webpage](https://pku-yuangroup.github.io/Helios-Page/) for more details. - [LightX2V](https://github.com/ModelTC/LightX2V), a lightweight and efficient video generation framework that integrates **Wan2.1** and **Wan2.2**, supporting multiple engineering acceleration techniques for fast inference. [LightX2V-HuggingFace](https://huggingface.co/lightx2v), offers a variety of Wan-based step-distillation models, quantized models, and lightweight VAE models.