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README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+---
+# Semantic-decoupled Spatial Partition Guided Point-supervised Oriented Object Detection
+
+[![arxiv](https://img.shields.io/badge/arXiv-2506.10601-479ee2.svg)](https://arxiv.org/pdf/2506.10601)
+[![Github](https://img.shields.io/badge/GitHub-SSP-blueviolet.svg)](https://github.com/antxinyuan/ssp)
+
+🔥 We appreciate the attention to our paper. The code is available at [Github repo](https://github.com/antxinyuan/ssp).
+
+> Production from Institute of Computing Technology, Chinese Academy of Sciences.
+
+> Primary contact: Xinyuan Liu ( liuxinyuan21s@ict.ac.cn ).
+
+## TL;DR
+This repository contains the source code of [**Semantic-decoupled Spatial Partition Guided Point-supervised Oriented Object Detection**](https://arxiv.org/pdf/2506.10601).
+
+To tackle inadequate sample assignment and instance confusion in point-supervised oriented object detection for remote sensing dense scenes, we propose SSP (Semantic-decoupled Spatial Partition), a framework integrating rule-driven prior injection and data-driven label purification. Its core innovations include pixel-level spatial partition for sample assignment and semantic-modulated box extraction for pseudo-label generation. 
+
+
+### Pseudo-label performance
+All pseudo-labeling results are available in [pseudo_labels](https://huggingface.co/antxinyuan/SSP/blob/main/pseudo_labels.zip).
+
+| Dataset | mAP | mIoU | ann_file |
+| :-: | :-: | :-: | :-: | 
+| DOTA-v1.0 | 34.95 |49.03 | pseudo_labels/ssp_dotav10_hybrid/ |
+| DOTA-v1.5 | 28.89 | 44.92 | pseudo_labels/ssp_dotav15_hybrid/ |
+| DOTA-v2.0 | 24.72 | 41.93 | pseudo_labels/ssp_dotav20_hybrid/ |
+
+### Detectors performance
+| Dataset | Config | Log | Checkpoint | mAP(paper) | mAP(reproduced) |
+| :-: | :-: | :-: | :-: | :-: | :-: |  
+| SSP(RFOCS) | [config](https://github.com/antxinyuan/ssp/blob/main/configs/ssp/rfcos_ssp_dotav10.py) | [hugging face](https://huggingface.co/antxinyuan/SSP/blob/main/logs/rfcos_ssp_dotav10.json) |  [hugging face](https://huggingface.co/antxinyuan/SSP/blob/main/models/rfcos_ssp_dotav10-4c17ff33.pth) | 45.78 | 45.82 |
+| SSP(ORCNN) | [config](https://github.com/antxinyuan/ssp/blob/main/configs/ssp/orcnn_ssp_dotav10.py) |  [hugging face](https://huggingface.co/antxinyuan/SSP/blob/main/logs/orcnn_ssp_dotav10.json) | [hugging face](https://huggingface.co/antxinyuan/SSP/blob/main/models/orcnn_ssp_dotav10-2df034d3.pth) | 47.86 | 48.81 |
+| SSP(ReDet) | [config](https://github.com/antxinyuan/ssp/blob/main/configs/ssp/orcnn_ssp_dotav20.py) |  [hugging face](https://huggingface.co/antxinyuan/SSP/blob/main/logs/redet_ssp_dotav10.json) | [hugging face](https://huggingface.co/antxinyuan/SSP/blob/main/models/redet_ssp_dotav10-eed2738e.pth) | 48.50 | 49.02 |
+
+## 🖊️ Citation
+
+If you find this work helpful for your research, please consider giving this repo a star ⭐ and citing our papers:
+
+
+## Citation
+If this work is helpful for your research, please consider citing the following BibTeX entry.
+
+``` bibtex
+@misc{liu2025ssp,
+      title={Semantic-decoupled Spatial Partition Guided Point-supervised Oriented Object Detection}, 
+      author={Xinyuan Liu and Hang Xu and Yike Ma and Yucheng Zhang and Feng Dai},
+      year={2025},
+      eprint={2506.10601},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2506.10601}, 
+}
+
+@inproceedings{xu2024acm,
+  title={Rethinking boundary discontinuity problem for oriented object detection},
+  author={Xu, Hang and Liu, Xinyuan and Xu, Haonan and Ma, Yike and Zhu, Zunjie and Yan, Chenggang and Dai, Feng},
+  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
+  pages={17406--17415},
+  year={2024}
+}
+
+```
+
+## Related resources
+
+We acknowledge all the open-source contributors for the following projects to make this work possible:
+- [PointOBB-v2](https://github.com/VisionXLab/PointOBB-v2)
+- [MMRotate](https://github.com/open-mmlab/mmrotate)