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  # JL1-CD: A New Benchmark for Remote Sensing Change Detection and a Robust Multi-Teacher Knowledge Distillation Framework
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  Code: https://github.com/circleLZY/MTKD-CD.
 
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+ ---
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+ license: mit
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+ library_name: pytorch
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+ pipeline_tag: image-to-image
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+ ---
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  # JL1-CD: A New Benchmark for Remote Sensing Change Detection and a Robust Multi-Teacher Knowledge Distillation Framework
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+ This repository contains the model presented in the paper [JL1-CD: A New Benchmark for Remote Sensing Change Detection and a Robust Multi-Teacher Knowledge Distillation Framework](https://arxiv.org/pdf/2502.13407). This model utilizes a multi-teacher knowledge distillation (MTKD) framework for change detection (CD) in remote sensing images.
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+ ## Dataset
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+ The JL1-CD dataset is publicly available and can be downloaded from:
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+ - [Google Drive](https://drive.google.com/drive/folders/1ELoqx7J3GrEFMX5_rRynMjW9-Poxz3Uu?usp=sharing)
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+ - [Baidu Disk](https://pan.baidu.com/s/1_vcO4c5DM5LDuOqLwLrWJg?pwd=5byn)
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+ - [Hugging Face](https://huggingface.co/datasets/circleLZY/JL1-CD)
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+ ## Usage
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+ ### Install
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+ To set up the environment, follow the installation instructions provided in the [OpenCD repository](https://github.com/likyoo/open-cd).
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+ ### Training
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+ The training process for the MTKD framework consists of three steps. Below, we use the **Changer-MiT-b0** model as an example:
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+ #### Step 1: Train the original model
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+ #### Step 2: Train teacher models for different CAR partitions (e.g., 3 partitions)
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+ #### Step 3: Train the student model
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+ ### Testing
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+ #### Checkpoints
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+ You can download checkpoint files from:
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+ - [Baidu Disk](https://pan.baidu.com/s/1F5MIGCCiNHFifNl_kDiklA?pwd=4tid)
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+ - [Hugging Face](https://huggingface.co/circleLZY/MTKD)
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+ ## Citation
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+ If you find the JL1-CD dataset or our work useful in your research, please consider citing our paper:
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+ ```bibtex
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+ @article{liu2025jl1,
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+ title={JL1-CD: A New Benchmark for Remote Sensing Change Detection and a Robust Multi-Teacher Knowledge Distillation Framework},
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+ author={Liu, Ziyuan and Zhu, Ruifei and Gao, Long and Zhou, Yuanxiu and Ma, Jingyu and Gu, Yuantao},
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+ journal={arXiv preprint arXiv:2502.13407},
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+ year={2025}
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+ }
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+ ```
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  Code: https://github.com/circleLZY/MTKD-CD.