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SegEarth-R2: Towards Comprehensive Language-guided Segmentation for Remote Sensing Images


  • 05/24/2026: The code is released!
  • 05/23/2026: LaSeRS dataset is released on HuggingFace

🔧 Usage:

Follow the guidelines below to set up, train and evaluate:

  • Preparation ⚙️: Instructions for organizing datasets and pretrained weights for proper model training and inference.
  • Installation 💻: Set up the segearthr2 conda environment, install dependencies, and clone the repo.
  • Training 🏋️‍♂️: Run scripts/train.sh with DeepSpeed, modifying parameters like data and model paths for training.
  • Evaluation 🎯: Run scripts/eval.sh to evaluate the model, updating paths as needed.

⭐️ Citation

If you find this project useful, welcome to cite us.

@article{xin2025segearth,
  title={SegEarth-R2: Towards Comprehensive Language-guided Segmentation for Remote Sensing Images},
  author={Xin, Zepeng and Li, Kaiyu and Chen, Luodi and Li, Wanchen and Xiao, Yuchen and Qiao, Hui and Zhang, Weizhan and Meng, Deyu and Cao, Xiangyong},
  journal={arXiv preprint arXiv:2512.20013},
  year={2025}
}

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[CVPR 2026 Highlight] SegEarth-R2: Towards Comprehensive Language-guided Segmentation for Remote Sensing Images

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