# LoFTR: Detector-Free Local Feature Matching with Transformers (WIP)
### [Project Page](https://zju3dv.github.io/loftr) | [Paper (TBD)](https://arxiv.org/pdf/2104.15838.pdf)

> LoFTR: Detector-Free Local Feature Matching with Transformers
> [Jiaming Sun](https://jiamingsun.ml)<sup>*</sup>, [Zehong Shen](zehongs.github.io)<sup>*</sup>, [Yu'ang Wang](https://github.com/angshine)<sup>*</sup>, [Hujun Bao](http://www.cad.zju.edu.cn/bao/), [Xiaowei Zhou](http://www.cad.zju.edu.cn/home/xzhou/)
> CVPR 2021

<!-- ![monocular](https://zju3dv.github.io/neuralbody/images/monocular.gif) -->


<br/>

We plan to release the code within the next week, stay tuned. In the meanwhile, discussions are welcomed in the [discussion panel](https://github.com/zju3dv/LoFTR/discussions).


## Citation

If you find this code useful for your research, please use the following BibTeX entry.

```
@article{sun2021loftr,
  title={{LoFTR}: Detector-Free Local Feature Matching with Transformers},
  author={Sun, Jiaming and Shen, Zehong and Wang, Yuang and Bao, Hujun and Zhou, Xiaowei},
  journal={CVPR},
  year={2021}
}
```

<!-- ## Acknowledgment

This repo is built based on the Mask R-CNN implementation from [maskrcnn-benchmark](https://github.com/facebookresearch/maskrcnn-benchmark), and we also use the pretrained Stereo R-CNN weight from [here](https://drive.google.com/file/d/1rZ5AsMms7-oO-VfoNTAmBFOr8O2L0-xt/view?usp=sharing) for initialization. -->


## Copyright
This work is affiliated with ZJU-SenseTime Joint Lab of 3D Vision, and its intellectual property belongs to SenseTime Group Ltd.

```
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Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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    http://www.apache.org/licenses/LICENSE-2.0

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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
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