Improve dataset card: add metadata, paper link, and project info

README.md

@@ -1,3 +1,30 @@
----
-license: mit
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+---
+license: mit
+task_categories:
+- image-to-3d
+---
+
+# VolSplat Dataset
+
+This repository contains preprocessed data for the paper [VolSplat: Rethinking Feed-Forward 3D Gaussian Splatting with Voxel-Aligned Prediction](https://huggingface.co/papers/2509.19297).
+
+[**Project Page**](https://lhmd.top/volsplat/) | [**GitHub**](https://github.com/ziplab/VolSplat) | [**Models**](https://huggingface.co/lhmd/VolSplat)
+
+## Introduction
+
+VolSplat is a new multi-view feed-forward paradigm for 3D Gaussian Splatting (3DGS) that replaces pixel alignment with voxel-aligned Gaussians. By directly predicting Gaussians from a predicted 3D voxel grid, it overcomes pixel alignment's reliance on error-prone 2D feature matching, ensuring robust multi-view consistency and enabling adaptive control over density based on 3D scene complexity.
+
+This repository provides preprocessed, torch-compatible versions of the **RealEstate10K (RE10K)** and **ACID** datasets used for training and evaluating the VolSplat models.
+
+## Citation
+
+If you find this dataset or the VolSplat method useful for your research, please consider citing:
+
+```bibtex
+@article{wang2025volsplat,
+  title={VolSplat: Rethinking Feed-Forward 3D Gaussian Splatting with Voxel-Aligned Prediction},
+  author={Wang, Weijie and Chen, Yeqing and Zhang, Zeyu and Liu, Hengyu and Wang, Haoxiao and Feng, Zhiyuan and Qin, Wenkang and Chen, Feng and Zhu, Zheng and Chen, Donny Y. and Zhuang, Bohan},
+  journal={arXiv preprint arXiv:2509.19297},
+  year={2025}
+}
+```