---
license: apache-2.0
---
# EVL: Egocentric Voxel Lifting

[[paper](https://arxiv.org/abs/2406.10224)]

## Intro

Egocentric Voxel Lifting (EVL) is a baseline model for 3D object detection and surface reconstruction.
EVL is trained on a large simulation dataset [Aria Synthetic Enviroments](https://www.projectaria.com/datasets/ase/).
EVL leverages egocentric modalities and inherits foundational capabilities from 2D foundation models.

<img src="assets/efm3d.png">

## Usage

Please refer to the [EFM3D](https://github.com/facebookresearch/efm3d) repo for installation and how to use the model

## Citing EVL

```
@article{straub2024efm3d,
  title={EFM3D: A Benchmark for Measuring Progress Towards 3D Egocentric Foundation Models},
  author={Straub, Julian and DeTone, Daniel and Shen, Tianwei and Yang, Nan and Sweeney, Chris and Newcombe, Richard},
  journal={arXiv preprint arXiv:2406.10224},
  year={2024}
}
```

## License

EVL is released by Meta under the [Apache 2.0 license](LICENSE).