MTLDesc (Local features detection and description)
Implementation of "MTLDesc: Looking Wider to Describe Better " (AAAI 2022).
Keywords: Local features detection and description; local descriptors; image matching.
To do：
- Evaluation code for MTLDesc.
- Trained model and Training dataset.
- Training code.
- A more efficient version at https://github.com/vignywang/AWDesc.
Requirement
pip install -r requirement.txt,
Quick start
HPatches Image Matching Benchmark
1.Download the trained model: https://drive.google.com/file/d/1qrvdd3KVYFl6EwH8s5IS5p_Hs26xIKRD/view?usp=sharing and place it in the "ckpt/mtldesc".
2.Download the HPatches dataset：
cd evaluation_hpatch/hpatches_sequences
bash download.sh
3.Extract local descriptors：
cd evaluation_hpatch
CUDA_VISIBLE_DEVICES=0 python export.py --tag [Descriptor_suffix_name] --top-k 10000 --output_root [out_dir] --config ../configs/MTLDesc_eva.yaml
4.Evaluation
cd evaluation_hpatch/hpatches_sequences
jupyter-notebook
run HPatches-Sequences-Matching-Benchmark.ipynb
Training
Download dataset: https://drive.google.com/file/d/1Uz0hVFPxWsE71V77kXZ973iY2GuXC20b/view?usp=sharing
Set the dataset path in the configuration file configs/MTLDesc_train.yaml
mega_image_dir: /data/Mega_train/image #images
mega_keypoint_dir: /data/Mega_train/keypoint #keypoints
mega_despoint_dir: /data/Mega_train/despoint #descriptor correspondence points
python train.py --gpus 0 --configs configs/MTLDesc_train.yaml --indicator mtldesc
Citation
@inproceedings{wang2022mtldesc,
title={MTLDesc: Looking Wider to Describe Better},
author={Wang, Changwei and Xu, Rongtao and Zhang, Yuyang and Xu, Shibiao and Meng, Weiliang and Fan, Bin and Zhang, Xiaopeng},
booktitle={AAAI},
year={2022},
organization={AAAI Press}
}