File size: 2,599 Bytes
0dffd4c
a13367a
0dffd4c
 
 
 
 
 
 
 
 
e192528
 
 
 
 
 
 
 
 
 
 
 
 
a13367a
e192528
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
44ab288
 
 
 
e192528
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
---
license: apache-2.0
library_name: diffusers
pipeline_tag: image-to-video
tags:
  - normal-estimation
  - video
  - diffusion
  - svd
---

# NormalCrafter — Video Normal Map Estimation

Mirror of [Yanrui95/NormalCrafter](https://huggingface.co/Yanrui95/NormalCrafter) hosted by [AEmotionStudio](https://huggingface.co/AEmotionStudio) for use with [ComfyUI-FFMPEGA](https://github.com/AEmotionStudio/ComfyUI-FFMPEGA).

## Model Description

NormalCrafter generates **temporally consistent surface normal maps** from video using a Stable Video Diffusion (SVD) backbone fine-tuned for normal estimation. Unlike image-based methods (e.g., Marigold), NormalCrafter operates natively on video sequences, producing smooth frame-to-frame normals without flickering.

## Key Features

- **Video-native**: Processes temporal sequences for coherent normals across frames
- **SVD backbone**: Built on `stabilityai/stable-video-diffusion-img2vid-xt`
- **High resolution**: Supports up to 1024px inference
- **Apache-2.0 Licensed**: Free for commercial and personal use

## Model Files

| File | Size | Description |
|------|------|-------------|
| `unet/diffusion_pytorch_model.safetensors` | 3.05 GB | Fine-tuned UNet for normal estimation |
| `image_encoder/model.fp16.safetensors` | 1.26 GB | CLIP image encoder (fp16) |
| `vae/diffusion_pytorch_model.safetensors` | 196 MB | VAE decoder |

## Usage in ComfyUI-FFMPEGA

NormalCrafter is available as:
- **Standalone skill**: `normalcrafter` in the FFMPEGA agent
- **No-LLM mode**: Select `normalcrafter` in the agent node dropdown
- **AI Relighting**: Enable "Use NormalCrafter" in the Video Editor's Relight panel for physically-based relighting

## Citation

```bibtex
@article{normalcrafter2024,
  title={NormalCrafter: Learning Temporally Consistent Normals from Video Diffusion Priors},
  author={Yanrui Bin and Wenbo Hu and Haoyuan Wang and Xinya Chen and Bing Wang},
  year={2024}
}
```

## License

- **Model weights** (this repo): **Apache-2.0** — matching the upstream [Yanrui95/NormalCrafter](https://huggingface.co/Yanrui95/NormalCrafter) HuggingFace repo. See [LICENSE](LICENSE).
- **Source code**: **MIT** — as published at [Binyr/NormalCrafter](https://github.com/Binyr/NormalCrafter) on GitHub.

Both licenses are permissive and allow commercial use.

## Links

- **Paper**: [NormalCrafter](https://github.com/Binyr/NormalCrafter)
- **Upstream weights**: [Yanrui95/NormalCrafter](https://huggingface.co/Yanrui95/NormalCrafter)
- **ComfyUI-FFMPEGA**: [AEmotionStudio/ComfyUI-FFMPEGA](https://github.com/AEmotionStudio/ComfyUI-FFMPEGA)