Here, we provide the official pytorch implementation of the paper "Adjacent-level Feature Cross-Fusion with 3D CNN for Remote Sensing Image Change Detection".
- python 3.9.12
- numpy 1.23.1
- pytorch 1.12.1
- torchvision 0.13.1
"""
Change detection data set with pixel-level binary labels;
├─A
├─B
├─label
└─list
├─train.txt
├─val.txt
├─test.txt
"""
A: Images of T1 time
B: Images of T2 time
label: label maps
list: contrains train.txt, val.txt, and test.txt. each fild records the name of image paris (XXX.png).
WHU-CD: https://study.rsgis.whu.edu.cn/pages/download/building_dataset.html
LEVIR-CD: https://justchenhao.github.io/LEVIR/
SYSU-CD: https://github.com/liumency/SYSU-CD
train.py
Test.py
The code is released for non-commercial and research purposes only. For commercial purposes, please contact the authors.
If you find this work interesting in your research, please cite our paper as follow:
@