Add model card, pipeline tag, and links to paper/code

README.md

@@ -1,3 +1,26 @@
----
-license: apache-2.0
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+---
+license: apache-2.0
+pipeline_tag: video-text-to-text
+---
+
+# VEGA-3D (Video Extracted Generative Awareness)
+
+VEGA-3D is a plug-and-play framework that repurposes a pre-trained video diffusion model as a Latent World Simulator to enrich Multimodal Large Language Models (MLLMs) with implicit 3D spatial priors for scene understanding, spatial reasoning, and embodied decision making.
+
+More details can be found in the paper: [Generation Models Know Space: Unleashing Implicit 3D Priors for Scene Understanding](https://huggingface.co/papers/2603.19235).
+
+* **Project Page:** [https://h-embodvis.github.io/VEGA-3D/](https://h-embodvis.github.io/VEGA-3D/)
+* **Repository:** [https://github.com/H-EmbodVis/VEGA-3D](https://github.com/H-EmbodVis/VEGA-3D)
+
+## Citation
+
+If you find VEGA-3D useful in your research, please consider citing:
+
+```bibtex
+@inproceedings{wu2026vega,
+      title={Generation Models Know Space: Unleashing Implicit 3D Priors for Scene Understanding},
+      author={Xianjin Wu and Dingkang Liang and Tianrui Feng and Kui Xia and Yumeng Zhang and Xiaofan Li and Xiao Tan and Xiang Bai},
+      booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
+      year={2026}
+}
+```