Zengtudor/Wan2.1
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Author SHA1 Message Date
ariaemaan
8ff6f83358
Merge 0543adc653 into e4f90fa81f 2025-12-13 19:38:08 +01:00
Shiwei Zhang
e4f90fa81f
Update community works section in README.md 2025-12-10 21:13:53 +08:00
Shiguang Ai
841fe5237b
When frame_num is changed from 81 the tensor does not match (#533) 2025-12-02 14:53:33 +08:00
2 changed files with 2 additions and 1 deletions
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1
README.md
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@ -36,6 +36,7 @@ In this repository, we present **Wan2.1**, a comprehensive and open suite of vid
## Community Works ## Community Works
If your work has improved **Wan2.1** and you would like more people to see it, please inform us. If your work has improved **Wan2.1** and you would like more people to see it, please inform us.
- [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.
- [EchoShot](https://github.com/JoHnneyWang/EchoShot), a native multi-shot portrait video generation model based on **Wan2.1-T2V-1.3B**, allows generation of multiple video clips featuring the same character as well as highly flexible content controllability. Refer to [their project page](https://johnneywang.github.io/EchoShot-webpage/) for more information. - [EchoShot](https://github.com/JoHnneyWang/EchoShot), a native multi-shot portrait video generation model based on **Wan2.1-T2V-1.3B**, allows generation of multiple video clips featuring the same character as well as highly flexible content controllability. Refer to [their project page](https://johnneywang.github.io/EchoShot-webpage/) for more information.
- [AniCrafter](https://github.com/MyNiuuu/AniCrafter), a human-centric animation model based on **Wan2.1-14B-I2V**, controls the Video Diffusion Models with 3DGS Avatars to insert and animate anyone into any scene following given motion sequences. Refer to the [project page](https://myniuuu.github.io/AniCrafter) for more examples. - [AniCrafter](https://github.com/MyNiuuu/AniCrafter), a human-centric animation model based on **Wan2.1-14B-I2V**, controls the Video Diffusion Models with 3DGS Avatars to insert and animate anyone into any scene following given motion sequences. Refer to the [project page](https://myniuuu.github.io/AniCrafter) for more examples.
- [HyperMotion](https://vivocameraresearch.github.io/hypermotion/), a human image animation framework based on **Wan2.1**, addresses the challenge of generating complex human body motions in pose-guided animation. Refer to [their website](https://vivocameraresearch.github.io/magictryon/) for more examples. - [HyperMotion](https://vivocameraresearch.github.io/hypermotion/), a human image animation framework based on **Wan2.1**, addresses the challenge of generating complex human body motions in pose-guided animation. Refer to [their website](https://vivocameraresearch.github.io/magictryon/) for more examples.

2
wan/image2video.py
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@ -207,7 +207,7 @@ class WanI2V:
generator=seed_g, generator=seed_g,
device=self.device) device=self.device)
msk = torch.ones(1, 81, lat_h, lat_w, device=self.device) msk = torch.ones(1, F, lat_h, lat_w, device=self.device)
msk[:, 1:] = 0 msk[:, 1:] = 0
msk = torch.concat([ msk = torch.concat([
torch.repeat_interleave(msk[:, 0:1], repeats=4, dim=1), msk[:, 1:] torch.repeat_interleave(msk[:, 0:1], repeats=4, dim=1), msk[:, 1:]