Wan 2.2 Fun Control - How To Use It? Any Good For Making Video?
Added 2025-08-13 13:00:20 +0000 UTC
Tutorial Video : https://youtu.be/b2yLOIWzqGw
For Patreon Supporters, New update for Long length Looping Gen : https://www.patreon.com/posts/136390097
In this video, we dive into WAN 2.2 Fun Control, the latest AI video model from Alibaba Pal, designed for precise motion control and video editing using reference footage. The creator explores how to use the WAN Video Wrapper in ComfyUI to generate consistent, high-quality AI videos with controllable character movements, camera motions, and scene stability.
The video covers advanced workflows such as using Flux Context to modify reference frames, applying Depth Anything V2 as a ControlNet for better depth awareness, and leveraging context chunking to generate longer video by splitting the sequence into manageable segments. You’ll also see real-world tests comparing different input methods, including pose consistency issues when using DW Pose and how editing the first and last frames with inpainting techniques dramatically improves output quality. This is a hands-on guide for creators who want to go beyond basic image-to-video generation and start building structured, controllable AI-driven animations.
Who is This Content Suitable For?
This content is ideal for:
AI video creators and digital artists looking to generate controlled, consistent AI-generated videos.
ComfyUI users who want to master the WAN Video Wrapper and integrate it with tools like Flux Context, ControlNet, and T2I adapters.
Developers and researchers experimenting with motion control, video-to-video generation, and AI-based animation pipelines.
Content creators interested in AI filmmaking, character animation, and reference-guided video synthesis.
Anyone exploring WAN 2.2 Fun Control, inpainting workflows, or long-sequence AI video generation.
Why Does This Matter?
As AI video generation advances, control and consistency are becoming the biggest challenges. While many models can generate a few seconds of impressive motion, they often fail when it comes to maintaining character pose, scene composition, or object stability over time. WAN 2.2 Fun Control introduces new features like context chunking, reference-based motion guidance, and inpainting for frame editing, which allow creators to take more control over the output. This video demonstrates practical workflows that bridge the gap between experimental AI tools and usable production techniques, helping creators understand how to build reliable, repeatable processes for generating AI video content that looks intentional and professional.
Resources:
Alibaba-pai HuggingFace : https://huggingface.co/alibaba-pai
Control model: https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-Control
FP8 : https://huggingface.co/Kijai/WanVideo_comfy_fp8_scaled/tree/main/Fun
ComfyUI-WanVideoWrapper : https://github.com/kijai/ComfyUI-WanVideoWrapper
Inpainting model: https://huggingface.co/alibaba-pai/Wan2.2-Fun-A14B-InP
Attached workflow of Wan 2.2 Fun Control basic and Flux Kontext + Fun Control :
