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🛰️ Official repository of paper "RemoteCLIP: A Vision Language Foundation Model for Remote Sensing" (IEEE TGRS)
| Date | Stars |
|---|---|
| 2026-07-31 | 579 |
| 2026-08-06 | 581 |
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<div align="center"> ## [RemoteCLIP🛰️: A Vision Language Foundation Model for Remote Sensing](https://arxiv.org/abs/2306.11029) [Fan Liu (刘凡)](https://multimodality.group/author/%E5%88%98%E5%87%A1/)✉ * <img src="assets/hhu_logo.png" alt="Logo" width="15">, [Delong Chen (陈德龙)](https://chendelong.world/)✉ * <img src="assets/hkust_logo.png" alt="Logo" width="10">, [Zhangqingyun Guan (管张青云)](https://github.com/gzqy1026) <img src="assets/hhu_logo.png" alt="Logo" width="15"> [Xiaocong Zhou (周晓聪)](https://multimodality.group/author/%E5%91%A8%E6%99%93%E8%81%AA/) <img src="assets/hhu_logo.png" alt="Logo" width="15">, [Jiale Zhu (朱佳乐)](https://multimodality.group/author/%E6%9C%B1%E4%BD%B3%E4%B9%90/) <img src="assets/hhu_logo.png" alt="Logo" width="15">, [Qiaolin Ye (业巧林)](https://it.njfu.edu.cn/szdw/20181224/i14059.html) <img src="assets/nfu_logo.png" alt="Logo" width="15">, Liyong Fu (符利勇) <img src="assets/caf_logo.jpg" alt="Logo" width="15">, [Jun Zhou (周峻)](https://experts.griffith.edu.au/7205-jun-zhou) <img src="assets/griffith_logo.png" alt="Logo" width="15"> <img src="assets/hhu_logo_text.png" alt="Logo" width="100"> <img src="assets/hkust_logo_text.png" alt="Logo" width="100"> <img src="assets/nfu_logo_text.jpg" alt="Logo" width="50"> <img src="assets/caf_logo.jpg" alt="Logo" width="40"> <img src="assets/griffith_logo_text.png" alt="Logo" width="90"> \* *Equal Contribution* </div> ### News - **2024/04/26**: The training dataset of RemoteCLIP (RET-3, SEG-4, DET-10) is released on 🤗HuggingFace, see [[gzqy1026/RemoteCLIP](https://huggingface.co/datasets/gzqy1026/RemoteCLIP)]. - **2024/04/03**: Our RemoteCLIP paper has been accepted by IEEE Transactions on Geoscience and Remote Sensing (TGRS) [[doi](https://ieeexplore.ieee.org/document/10504785)]. - **2024/03/01**: RemoteCLIP joined the leaderboard on [paperswithcode.com](https://paperswithcode.com/paper/remoteclip-a-vision-language-foundation-model) [](https://paperswithcode.com/sota/cross-modal-retrieval-on-rsicd?p=remoteclip-a-vision-language-foundation-model) [](https://paperswithcode.com/sota/cross-modal-retrieval-on-rsitmd?p=remoteclip-a-vision-language-foundation-model) - **2023/12/01**: You can now auto-label remote sensing datasets with RemoteCLIP using the [`autodistill-remote-clip`](https://github.com/autodistill/autodistill-remote-clip) extension in the [Autodistill](https://github.com/autodistill/autodistill) framework, thanks [James Gallagher](https://jamesg.blog/) from Roboflow! - **2023/11/07**: To facilitate reproducing RemoteCLIP's SOTA image-text retrieval results, we have prepared a `retrieval.py` script for retrieval evaluation on RSITMD, RSICD, and UCM datasets. Please see the [Retrieval Evaluation](#retrieval-evaluation) section for details. - **2023/07/27**: We make pretrained checkpoints of RemoteCLIP models (`ResNet-50`, `ViT-base-32`, and `ViT-large-14`) available! We converted the weights to the [`OpenCLIP`](https://github.com/mlfoundations/open_clip) format, such that loading and using RemoteCLIP is extremely easy! Please see the [Load RemoteCLIP](#load-remoteclip) section for details. We also provide a Jupyter Notebook [demo.ipynb](demo.ipynb). You can also [](https://colab.research.google.com/github/ChenDelong1999/RemoteCLIP/blob/main/RemoteCLIP_colab_demo.ipynb), thanks [Dr. Gordon McDonald](https://github.com/gdmcdonald) from the University of
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matched fp:f090422e63293a33, desc:vision-language