---
title: SHeaP - Self-Supervised Head Geometry Predictor
emoji: 🐑
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: "5.50.0"
app_file: gradio_demo.py
pinned: false
license: mit
---

# SHeaP: Self-Supervised Head Geometry Predictor Learned via 2D Gaussians

Upload an image or video to predict head geometry and render a 3D FLAME mesh overlay!

**Liam Schoneveld, Zhe Chen, Davide Davoli, Jiapeng Tang, Saimon Terazawa, Ko Nishino, Matthias Nießner**

- [Project Page](https://nlml.github.io/sheap)
- [Paper](https://arxiv.org/abs/2504.12292)
- [GitHub Repository](https://github.com/nlml/sheap)

## About

SHeaP learns to predict head geometry (FLAME parameters) from a single image by predicting and rendering 2D Gaussians.

The output shows three views:
- **Left**: Original cropped face
- **Center**: Rendered FLAME mesh
- **Right**: Mesh overlaid on original

## Setup Instructions

Before deploying to Hugging Face Spaces, you need to:

1. Download the FLAME model from [FLAME 2020](https://flame.is.tue.mpg.de/)
2. Convert it using `python convert_flame.py`
3. Include the `FLAME2020/` directory with the required files:
   - `generic_model.pt`
   - `eyelids.pt`
   - `flame_landmark_idxs_barys.pt`
4. Include the `models/` directory with:
   - `model_expressive.pt`
   - `model_paper.pt`
   - `model_lightweight.pt` (if available)