facebookresearch / GenIA

# GenIA
### Generative Reconstruction with Test-Time Input Alignment
### Project Page | Paper
Stefano Esposito 1 ,
Naama Pearl 1 ,
Polina Karpikova 1 ,
Samuel Rota Bulò 2 ,
Lorenzo Porzi 2 ,
Peter Kontschieder 2 ,
Andreas Geiger 1 ,
Jonathon Luiten 3 
 1 Tübingen AI Center, University of Tübingen, 2 Meta, Zürich, 3 Meta, USA
GenIA reconstructs complete, detailed and input-aligned 3D objects from a single image,
a few views of a static scene, or a monocular video. It keeps the generative prior of
SAM 3D Objects frozen and **aligns it to the observations at inference time** with
geometric and photometric constraints: no retraining, no weight updates. The output is a
canonical object (Gaussians and a mesh) with per-frame poses and, for video, a
per-frame deformation.
## 🛠️ Installation
Requires conda, a CUDA 12.8 toolkit and an NVIDIA GPU.
 [code] 
## 🚀 Demo
`demo/data/` holds example inputs for the three settings:
 [code] 
Results are written to `results/`. To run your own data, add it as a new scene folder
under `demo/data/ /`, laid out like the examples, and pass `--scene `.
See docs/configuration.md for the configuration options.
## 📜 License
This project is licensed under the **Creative Commons Attribution-NonCommercial 4.0
International License (CC BY-NC 4.0)**. See the LICENSE file for details.
Third-party components keep their own licences, several of them non-commercial; see
THIRD_PARTY_LICENSES.md before any use.
## 📚 Citation
If you use this work in your research, please consider citing:
 [code] 
## 🙏 Acknowledgements
Built on SAM 3D Objects. Geometry
from MapAnything and
MoGe; dynamic shapes from
ActionMesh; rendering via
gsplat and
nvdiffrast.