Mast3r ViTLarge BaseDecoder 512 Catmlpdpt Metric

🚀 Grounding Image Matching in 3D with MASt3R

MASt3R enables grounding image matching in 3D, offering innovative solutions for 3D vision tasks.

🚀 Quick Start

To start using MASt3R, first install mast3r. Then you can load the model as follows.

💻 Usage Examples

Basic Usage

from mast3r.model import AsymmetricMASt3R
import torch

model = AsymmetricMASt3R.from_pretrained("naver/MASt3R_ViTLarge_BaseDecoder_512_catmlpdpt_nonmetric")

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)

📚 Documentation

@misc{mast3r_arxiv24,
      title={Grounding Image Matching in 3D with MASt3R}, 
      author={Vincent Leroy and Yohann Cabon and Jerome Revaud},
      year={2024},
      eprint={2406.09756},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

@inproceedings{dust3r_cvpr24,
      title={DUSt3R: Geometric 3D Vision Made Easy}, 
      author={Shuzhe Wang and Vincent Leroy and Yohann Cabon and Boris Chidlovskii and Jerome Revaud},
      booktitle = {CVPR},
      year = {2024}
}

📄 License

The code is distributed under the CC BY-NC-SA 4.0 License. See LICENSE for more information.
For the checkpoints, make sure to agree to the license of all the public training datasets and base checkpoints we used, in addition to CC-BY-NC-SA 4.0.
The mapfree dataset license in particular is very restrictive. For more information, check CHECKPOINTS_NOTICE.

📦 Model Info

Gihub page: https://github.com/naver/mast3r/