Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021

Overview

LoFTR: Detector-Free Local Feature Matching with Transformers

Project Page | Paper


LoFTR: Detector-Free Local Feature Matching with Transformers
Jiaming Sun*, Zehong Shen*, Yu'ang Wang*, Hujun Bao, Xiaowei Zhou
CVPR 2021

demo_vid


Code release ETA

We plan to release the inference-only code and pretrained model within the upcoming week, stay tuned. The entire codebase for data pre-processing, training and validation is under major refactoring and will be released around June. Please subscribe to this discussion thread if you wish to be notified of the code release. In the meanwhile, discussions about the paper are welcomed in the discussion panel.

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}
}

Copyright

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

Copyright SenseTime. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Owner
ZJU3DV
ZJU3DV is a research group of State Key Lab of CAD&CG, Zhejiang University. We focus on the research of 3D computer vision, SLAM and AR.
ZJU3DV
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