Add dataset card for DL3DV-Res, including paper link, GitHub, and task categories

This PR populates the dataset card for the DL3DV-Res benchmark. It includes:
- A link to the associated paper: "GSFixer: Improving 3D Gaussian Splatting with Reference-Guided Video Diffusion Priors" (https://huggingface.co/papers/2508.09667).
- A link to the official GitHub repository: https://github.com/GVCLab/GSFixer.
- A link to the project page: https://gvclab.github.io/GSFixer/.
- Relevant task categories and tags in the metadata.
- A description of the dataset and sample usage for downloading.

README.md

@@ -0,0 +1,35 @@
+---
+task_categories:
+- image-to-video
+tags:
+- 3d
+- gaussian-splatting
+- artifact-restoration
+---
+
+# DL3DV-Res Benchmark
+
+[**Project Page**](https://gvclab.github.io/GSFixer/) | [**Paper**](https://huggingface.co/papers/2508.09667) | [**GitHub**](https://github.com/GVCLab/GSFixer)
+
+DL3DV-Res is a benchmark dataset introduced in the paper "GSFixer: Improving 3D Gaussian Splatting with Reference-Guided Video Diffusion Priors". It contains artifact frames rendered using low-quality 3D Gaussian Splatting (3DGS) from sparse views, and is designed for evaluating 3DGS artifact restoration and sparse-view 3D reconstruction.
+
+## Dataset Usage
+
+The DL3DV-Res benchmark data can be downloaded using the following command, as indicated in the official GitHub repository:
+
+```bash
+python download/download_data_hf.py
+```
+
+## Citation
+
+If you find this dataset useful for your research, please consider citing the original paper:
+
+```bibtex
+@article{yin2025gsfixer,
+  title={GSFixer: Improving 3D Gaussian Splatting with Reference-Guided Video Diffusion Priors},
+  author={Yin, Xingyilang and Zhang, Qi and Chang, Jiahao and Feng, Ying and Fan, Qingnan and Yang, Xi and Pun, Chi-Man and Zhang, Huaqi and Cun, Xiaodong},
+  journal={arXiv preprint arXiv:2508.09667},
+  year={2025}
+}
+```