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Direction-coded Temporal U-shape Module for Multiframe Infrared Small Target Detection
Pytorch implementation of our Direction-coded Temporal U-shape Module (DTUM). [Paper]
Requirements
- Python 3
- torch
- mmdet
- tqdm
- DCNv2
- scikit-image <br><br>
Datasets
NUDT-MIRSDT [Baidu download dir] (Extraction code: 5whn) is a synthesized dataset, which contains 120 sequences. We use 80 sequences for training and 20 sequences for test. We divide the test set into two subsets according to their SNR ((0, 3], (3, 10)).
In the test set, targets in 8 sequences are so weak (SNR lower than 3). It is very challenging to detect these targets.
Train on NUDT-MIRSDT Dataset
python train.py --model 'ResUNet_DTUM' --loss_func 'fullySup' --train 1 --test 0 --fullySupervised True
python train.py --model 'DNANet_DTUM' --loss_func 'fullySup1' --train 1 --test 0 --fullySupervised True --SpatialDeepSup False
Test on NUDT-MIRSDT Dataset
python train.py --model 'ResUNet_DTUM' --loss_func 'fullySup' --train 0 --test 1 --pth_path [trained model path]
Train on IRDST Dataset (or other datasets)
python train.py --dataset IRDST --align --model 'ResUNet_DTUM' --loss_func 'fullySup' --train 1 --test 0 --fullySupervised True
If the background in a sequence is not aligned, the parameter of "align" needs to be set to True. <br>
Results and Trained Models
Quantative Results
on NUDT-MIRSDT (SNR≤3)
| Model | Pd (x10(-2)) | Fa (x10(-5)) | AUC | |
|---|---|---|---|---|
| ALCNet +DTUM | 56.144 | 0.931 | 0.9489 | |
| Res-UNet+DTUM | 91.682 | 2.369 | 0.9921 | [Weights] |
| DNANet +DTUM | 85.444 | 1.118 | 0.9882 | |
| ISNet +DTUM | 50.662 | 0.646 | 0.9482 | |
| UIUNet +DTUM | 72.023 | 1.916 | 0.9933 |
on NUDT-MIRSDT (SNR＞3)
| Model | Pd (x10(-2)) | Fa (x10(-5)) | AUC | |
|---|---|---|---|---|
| ALCNet +DTUM | 99.500 | 2.370 | 0.9988 | |
| Res-UNet+DTUM | 100 | 3.415 | 0.9988 | [Weights] |
| DNANet +DTUM | 99.833 | 3.633 | 0.9988 | |
| ISNet +DTUM | 99.750 | 3.448 | 0.9988 | |
| UIUNet +DTUM | 99.833 | 3.578 | 0.9988 |
on NUDT-MIRSDT (all)
| Model | Pd (x10(-2)) | Fa (x10(-5)) | AUC | |
|---|---|---|---|---|
| ALCNet +DTUM | 86.235 | 1.798 | 0.9818 | |
| Res-UNet+DTUM | 97.455 | 2.999 | 0.9964 | [Weights] |
| DNANet +DTUM | 95.431 | 2.620 | 0.9951 | |
| ISNet +DTUM | 84.731 | 2.334 | 0.9816 | |
| UIUNet +DTUM | 91.324 | 2.917 | 0.9972 |
Citiation
@article{li2023direction,
title={Direction-Coded Temporal U-Shape Module for Multiframe Infrared Small Target Detection.},
journal={IEEE Transactions on Neural Networks and Learning Systems},
year={2023}
}
Contact
Welcome to raise issues or email to liruojing@nudt.edu.cn for any question.