Instructions to use PeppX/video-pid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use PeppX/video-pid with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("PeppX/video-pid", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| library_name: diffusers | |
| tags: | |
| - video | |
| - diffusion | |
| - vae | |
| - decoder | |
| - wan | |
| - pixel-space | |
| - pid | |
| pipeline_tag: image-to-video | |
| # Video-PiD: Pixel-Space Decoder for Wan 2.1 | |
| A small 3D pixel-space diffusion model that runs on top of Wan 2.1's VAE-decoded video frames to fix the "plastic" / waxy look of latent diffusion decoders. | |
| **Status: pre-alpha. No weights yet.** This repo will hold the trained checkpoints. The source code lives at [github.com/madxmoron/video-pid](https://github.com/madxmoron/video-pid). | |
| ``` | |
| Wan 2.1 1.3B T2V Video-PiD | |
| ββββββββββββ Wan-VAE ββββββββββββ residual ββββββββββββ | |
| β text ββββΆ decode ββββββΆβ pixel ββββΆ denoise βββΆβ pixel ββββΆ video | |
| β latent β (plastic) β frames β (4 steps) β frames β (sharp) | |
| ββββββββββββ ββββββββββββ ββββββββββββ | |
| ``` | |
| ## Why | |
| Latent diffusion decoders (Wan-VAE, SD-VAE, etc.) throw away high-frequency detail and re-introduce a "waxy" smoothness. Video-PiD is a tiny post-pass that re-denoises the decoded frames in pixel space, conditioning on the original latent, and outputs a residual that adds back the detail. | |
| Inspired by NVIDIA's [PiD](https://research.nvidia.com/labs/sil/projects/pid/) (image-only). We extend it to video, in 3D, as a plug-in for Wan 2.1. | |
| ## Roadmap | |
| - [ ] Architecture spec pinned (in progress) | |
| - [ ] Training run on Panda-70M / HD-VGGT | |
| - [ ] First checkpoint release (v0.1.0) | |
| - [ ] ComfyUI node | |
| See [github.com/madxmoron/video-pid/blob/main/docs/ROADMAP.md](https://github.com/madxmoron/video-pid/blob/main/docs/ROADMAP.md) for the full plan. | |
| ## License | |
| Apache 2.0. | |
| ## Citation | |
| ```bibtex | |
| @software{video_pid_2026, | |
| author = {madxmoron}, | |
| title = {Video-PiD: Pixel-Space Decoder for Wan 2.1}, | |
| year = {2026}, | |
| url = {https://github.com/madxmoron/video-pid} | |
| } | |
| ``` | |