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license: apache-2.0 |
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--- |
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# EVL: Egocentric Voxel Lifting |
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[[paper](https://arxiv.org/abs/2406.10224)] |
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## Intro |
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Egocentric Voxel Lifting (EVL) is a baseline model for 3D object detection and surface reconstruction. |
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EVL is trained on a large simulation dataset [Aria Synthetic Enviroments](https://www.projectaria.com/datasets/ase/). |
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EVL leverages egocentric modalities and inherits foundational capabilities from 2D foundation models. |
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<img src="assets/efm3d.png"> |
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## Usage |
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Please refer to the [EFM3D](https://github.com/facebookresearch/efm3d) repo for installation and how to use the model |
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## Citing EVL |
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``` |
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@article{straub2024efm3d, |
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title={EFM3D: A Benchmark for Measuring Progress Towards 3D Egocentric Foundation Models}, |
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author={Straub, Julian and DeTone, Daniel and Shen, Tianwei and Yang, Nan and Sweeney, Chris and Newcombe, Richard}, |
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journal={arXiv preprint arXiv:2406.10224}, |
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year={2024} |
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} |
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``` |
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## License |
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EVL is released by Meta under the [Apache 2.0 license](LICENSE). |
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