The Pytorch implementation for: “EfficientCD: A New Strategy For Change Detection Based With Bi-temporal Layers Exchanged[]([2407.15999/] EfficientCD: A New Strategy For Change Detection Based With Bi-temporal Layers Exchanged (arxiv.org)), Sijun Dong, Yuwei Zhu, Geng Chen, Xiaoliang Meng::yum::yum:
[EfficientCD](EfficientCD: A New Strategy For Change Detection Based With Bi-temporal Layers Exchanged | IEEE Journals & Magazine | IEEE Xplore) has been accepted in [IEEE TGRS](IEEE Xplore: IEEE Transactions on Geoscience and Remote Sensing)
check the configs
bash tools/train.sh
LEVIR-CD: 链接:https://pan.baidu.com/s/1epOgO-cw1gDsLdKwnb_Etw 提取码:k7hu
(This experimental setting is different from the experimental setting description of the LEVIR-CD dataset in the original paper. It adopts the same experimental setting method as the CLCD dataset, using random cutting training and sliding window prediction.)
WHUCD: 链接:https://pan.baidu.com/s/12_O_CdDemhidzNw1jJUwCA 提取码:u1md
CLCD: 链接: https://pan.baidu.com/s/1Ha4VR2KNhY0Mi7uaFinmWQ 提取码: viqe
If you use this code for your research, please cite our papers.
@ARTICLE{10608163,
author={Dong, Sijun and Zhu, Yuwei and Chen, Geng and Meng, Xiaoliang},
journal={IEEE Transactions on Geoscience and Remote Sensing},
title={EfficientCD: A New Strategy For Change Detection Based With Bi-temporal Layers Exchanged},
year={2024},
volume={},
number={},
pages={1-1},
keywords={Feature extraction;Remote sensing;Task analysis;Computational modeling;Transformers;Biological system modeling;Land surface;Change detection;feature interaction;Euclidean distance},
doi={10.1109/TGRS.2024.3433014}}
Our code is inspired and revised by open-mmlab/mmsegmentation, timm. Thanks for their great work!!