Add dataset card and metadata for SpaceSpan

README.md

@@ -1,3 +1,54 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+- video-text-to-text
+tags:
+- 3D
+- vision-language
+- spatial-intelligence
+---
+
+# SpaceSpan Dataset
+
+SpaceSpan is a large-scale dataset curated for aligning 3D proxy representations with Vision-Language Models (VLMs), introduced in the paper [Proxy3D: Efficient 3D Representations for Vision-Language Models via Semantic Clustering and Alignment](https://huggingface.co/papers/2605.08064).
+
+The dataset incorporates heterogeneous visual information into a unified format to support multi-stage training for developing spatial intelligence. It enables models to progress from simple image-text alignment to complex 3D reasoning tasks, such as 3D visual question answering (VQA) and visual grounding.
+
+[**Project Page**](https://wzzheng.net/Proxy3D) | [**GitHub**](https://github.com/Spacedreamer2384/Proxy3D) | [**Paper**](https://huggingface.co/papers/2605.08064)
+
+## Dataset Description
+
+The SpaceSpan dataset (specifically the SpaceSpan-318K version) supports four progressive training stages:
+- **Stage 1**: Initial spatial alignment.
+- **Stage 2-3**: Intermediate spatial reasoning development.
+- **Stage 4**: Full-scale 3D reasoning.
+
+### Directory Structure
+
+Based on the official repository, the dataset is typically organized as follows:
+
+```bash 
+data/               # Training and inference data
+├── icon_image_embeds_qwen25.pt
+├── number_image_embeds_qwen25.pt
+├── stage_1_train.json
+├── stage_2_train.json
+├── stage_3_train.json
+├── stage_4_train_318K.json
+├── pointmaps_wo_markers
+├── poses
+└── ... 
+```
+
+## Citation
+
+If you find this dataset useful for your research, please cite the following paper:
+
+```bibtex
+@article{proxy3d2026,
+  title={Proxy3D: Efficient 3D Representations for Vision-Language Models via Semantic Clustering and Alignment},
+  author={Jiang, Jerry and Sun, Haowen and Gudovskiy, Denis and Nakata, Yohei and Okuno, Tomoyuki and Keutzer, Kurt and Zheng Wenzhao},
+  journal={arXiv preprint arXiv:2605.08064},
+  year={2026}
+}
+```