Add task category and links to paper, project page, and code

This PR improves the dataset card by:
- Adding the `image-to-image` task category to the metadata.
- Linking the dataset to the paper, project page, and official GitHub repository.
- Including the official BibTeX citation.
- Organizing the content for better readability.

README.md

@@ -1,9 +1,18 @@
 ---
 license: mit
+task_categories:
+- image-to-image
 ---
-## CVPR 2026 Highlight--GOR-IS (https://applezyh.github.io/GOR-IS-project-page/)
+
+# GOR-IS Datasets
+
+[**Project Page**](https://applezyh.github.io/GOR-IS-project-page/) | [**Paper**](https://huggingface.co/papers/2605.00498) | [**GitHub**](https://github.com/applezyh/GOR-IS)
+
+This repository contains the datasets for **GOR-IS: 3D Gaussian Object Removal in the Intrinsic Space**, presented as a Highlight at CVPR 2026.
+
 We provide a comprehensive suite of datasets, including our proposed **GOR-IS-Synthetic** and **GOR-IS-Real**, along with additional real-world scenes (**Additional-Real**) sourced from Mip-NeRF 360 and Ref-Real, and synthetic scenes (**Additional-Synthetic**) featuring more complex inpainting textures. All datasets are fully preprocessed and contain the necessary components for our framework, enabling users to directly download, decompress, and use them without additional setup.
 
+## Dataset Organization
 The organization of the datasets is as follows:
 ```sh
 GOR-IS-datasets/
@@ -29,4 +38,15 @@ GOR-IS-datasets/
 │
 ├── additional-synthetic/
 │   ├── ...
+```
+
+## Citation
+If you find our work is helpful, please consider citing:
+```bibtex
+@inproceedings{zhao2026gor-is,
+  title={GOR-IS: 3D Gaussian Object Removal in the Intrinsic Space},
+  author={Yonghao Zhao and Yupeng Gao and Jian Yang and Jin Xie and Beibei Wang},
+  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
+  year={2026}
+}
 ```