This repo contains the official PyTorch code for ChangeBind.
ChangeBind utilizes a change encoder that leverages local and global feature representations to capture both subtle and large change feature information to precisely estimate the change regions.
pytorch 1.10.0
timm 0.4.12
opencv-python
tqdm
pillow
"""
Change detection data set with pixel-level binary labels;
├─A
├─B
├─label
└─list
"""
A
: images at time frame t1;
B
:images at time frame t2;
label
: label masks;
list
: contains train.txt, val.txt and test.txt
, each file records the image names (____.png) in the change detection dataset.
@inproceedings{changebind2024,
title={ChangeBind: A Hybrid Change Encoder for Remote Sensing Change Detection},
author={Noman, Mubashir and Fiaz, Mustansar and Cholakkal, Hisham},
booktitle={Arxiv},
year={2024}
}
Thanks to the codebases [ScratchFormer] [BIT] [ChangeFormer].
ScratchFormer: Remote Sensing Change Detection With Transformers Trained from Scratch
ELGCNet: Efficient Local-Global Context Aggregation for Remote Sensing Change Detection