MiniMax H3 Character-Motion R2V

This R2V workflow combines a character image, a scene image, and a motion video. It is designed for preserving the appearance of the person or character while transferring the movement pattern, stance changes, and performance rhythm from the video reference.

The workflow uses the MiniMax H3 local ComfyUI graph with the connected model, VAE, encoder, sampler, resolution, and video output chain shown in the JSON.

Main features:

- MiniMax H3 FL2VA diffusion model with video VAE and Qwen3-VL text encoding
- MiniMaxH3ReferenceToVideo route for character, scene, and motion references
- Character identity and scene composition can be described separately
- Motion reference controls steps, body alignment, gestures, and performance rhythm
- Connected 9:16 portrait widescreen resolution at the 0.4 megapixel setting
- 20-step simple scheduler with res_multistep sampling
- SaveVideo output for mobile and vertical video workflows

Suggested workflow:

Use the character image for identity, the scene image for environment, and the video only for motion. Keep those roles explicit in the prompt. Begin with a simple movement pattern, verify identity stability, then add more complex gestures or camera changes.

⚡ RunningHub Workflow

Try the workflow online right now - no installation required.
👉 Workflow: https://www.runninghub.ai/post/2084850873976578049?inviteCode=rh-v1111

If the results meet your expectations, you can later deploy it locally for customization.

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📵 Bilibili Updates (Mainland China & Asia-Pacific)

If you're in the Asia-Pacific region, you can watch the video below to see the workflow demonstration and creative breakdown.
📵 Bilibili Video: https://www.bilibili.com/video/BV1MrMk69Ejk/

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⚡ 打开下方链接即可在线体验，无需安装。
👉 工作流：https://www.runninghub.ai/post/2084850873976578049?inviteCode=rh-v1111

如果你觉得效果理想，也可以在本地进行自定义部署。

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📵 B站视频（中国大陆及亚洲地区）

如果你在中国大陆或亚洲地区，可以通过下面的视频查看工作流的实测效果与创作思路。
📵 B站视频：https://www.bilibili.com/video/BV1MrMk69Ejk/

我会在夸克网盘持续更新模型资源：
👉 https://pan.quark.cn/s/07bdc81784ce