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+ ---
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+ license: apache-2.0
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+ tags:
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+ - image-to-image
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+ - SAR
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+ - remote-sensing
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+ - diffusion
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+ - computer-vision
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+ ---
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+
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+ # E3Diff: SAR-to-Optical Image Translation
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+
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+ **🏆 1st Place - CVPR PBVS2025 Multi-modal Aerial View Image Challenge**
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+
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+ ## Model Description
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+
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+ E3Diff is an efficient end-to-end diffusion model for one-step SAR-to-Optical translation.
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+
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+ ### Key Features
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+ - **Real-time inference**: 0.17s per 256x256 image on A6000
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+ - **High quality**: 35% FID improvement over previous SOTA
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+ - **One-step sampling**: Unlike traditional diffusion (1000 steps)
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+
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+ ## Usage
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+
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+ ```python
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+ from huggingface_hub import hf_hub_download
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+ import torch
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+
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+ # Download weights
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+ weights = hf_hub_download(repo_id="Dhenenjay/E3Diff-SAR2Optical", filename="I700000_E719_gen.pth")
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+ ```
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @ARTICLE{10767752,
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+ author={Qin, Jiang and Zou, Bin and Li, Haolin and Zhang, Lamei},
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+ journal={IEEE Geoscience and Remote Sensing Letters},
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+ title={Efficient End-to-End Diffusion Model for One-step SAR-to-Optical Translation},
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+ year={2024},
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+ doi={10.1109/LGRS.2024.3506566}
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+ }
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+ ```
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+
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+ ## Links
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+ - [Paper](https://ieeexplore.ieee.org/document/10767752)
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+ - [GitHub](https://github.com/DeepSARRS/E3Diff)