Update README.md

README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+---
+
+# HYRET-CHANGE: A HYBRID RETENTIVE NETWORK FOR REMOTE SENSING CHANGE DETECTION
+
+[Mustansar Fiaz](https://sites.google.com/view/mustansarfiaz/home), [Mubashir Noman](https://scholar.google.com/citations?user=S6_CVskAAAAJ&hl=en),  [Hiyam Debary](https://www.linkedin.com/in/hiyam-debary/), [Kamran Ali](https://scholar.google.com/citations?user=JuQ_vNIAAAAJ&hl=en), [Hisham Cholakkal](https://hishamcholakkal.com/)
+
+[![paper](https://img.shields.io/badge/arXiv-Paper-<COLOR>.svg)](https://arxiv.org/pdf/2506.12836)
+[![GitHub Repo](https://img.shields.io/badge/GitHub-HyRect--Change-181717?logo=github)](https://github.com/mustansarfiaz/HyRect-Change)
+
+---
+### 🏆 Highlights
+
+- **HyRet-Change:** We propose a Siamese-based framework, which can seamlessly integrate the merits of convolution and retention mechanisms at multi-scale features to preserve critical information and enhance adaptability in complex scenes change detection (CD).  Specifically, we propose a hybrid plug-and-play feature difference module (FDM) to explore rich feature information utilizing both self-attention and convolution operations in a parallel way. This unique integration, at multi-scale features, leverages the
+advantages of both local features and long-range contextual information. We introduce a retention mechanism in our novel FDM to mitigate the limitations of standard self-attention.
+- **Local-Global (LG)-Interaction Module:** We introduce an adaptive interaction between local and global representations to exploit the intricate relationship contextually to strengthen the model’s ability to perceive meaningful changes while reducing the effect of pseudo-changes.
+- **Experiments:** Our extensive experimental study over three challenging CD datasets demonstrates the merits of our approach while achieving state-of-the-art performance.
+
+
+## Citation
+
+```
+@inproceedings{fiaz2025hyret,
+  title={HyRet-Change: A hybrid retentive network for remote sensing change detection},
+  author={Fiaz, Mustansar and Noman, Mubashir and Debary, Hiyam and Ali, Kamran and Cholakkal, Hisham},
+  booktitle={IGARSS 2025-2025 IEEE International Geoscience and Remote Sensing Symposium},
+  year={2025},
+  publisher={IEEE}
+}
+@inproceedings{noman2024changebind,
+  title={Changebind: A hybrid change encoder for remote sensing change detection},
+  author={Noman, Mubahsir and Fiaz, Mustansar and Cholakkal, Hisham},
+  booktitle={IGARSS 2024-2024 IEEE International Geoscience and Remote Sensing Symposium},
+  pages={8417--8422},
+  year={2024},
+  organization={IEEE}
+}
+@article{noman2024elgc,
+  title={ELGC-Net: Efficient local--global context aggregation for remote sensing change detection},
+  author={Noman, Mubashir and Fiaz, Mustansar and Cholakkal, Hisham and Khan, Salman and Khan, Fahad Shahbaz},
+  journal={IEEE Transactions on Geoscience and Remote Sensing},
+  volume={62},
+  pages={1--11},
+  year={2024},
+  publisher={IEEE}
+}
+@article{noman2024remote,
+  title={Remote sensing change detection with transformers trained from scratch},
+  author={Noman, Mubashir and Fiaz, Mustansar and Cholakkal, Hisham and Narayan, Sanath and Anwer, Rao Muhammad and Khan, Salman and Khan, Fahad Shahbaz},
+  journal={IEEE Transactions on Geoscience and Remote Sensing},
+  volume={62},
+  pages={1--14},
+  year={2024},
+  publisher={IEEE}
+}
+```
+
+### Contact
+
+If you have any question, please feel free to contact the authors. Mustansar Fiaz: [mustansar.fiaz@ibm.com](mailto:mustansar.fiaz@ibm.com) or Mubashir Noman: [mubashir.noman@mbzuai.ac.ae](mailto:mubashir.noman@mbzuai.ac.ae).
+
+## References
+Our code is based on [Changebind](https://github.com/techmn/changebind) repository. 
+We thank them for releasing their baseline code.