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README.md

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+<!-- # Spatial457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Multimodal Models -->
+e
+<h1 align="center">
+  <a href="https://arxiv.org/abs/2502.08636">
+    Spatial457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Multimodal Models
+  </a>
+</h1>
 
-# Spatial457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Multimodal Models
+<p align="center">
+  <a href=".">Xingrui Wang</a><sup>1</sup>,
+  <a href=".">Wufei Ma</a><sup>1</sup>,
+  <a href=".">Tiezheng Zhang</a><sup>1</sup>,
+  <a href=".">Celso M de Melo</a><sup>2</sup>,
+  <a href=".">Jieneng Chen</a><sup>1</sup>,
+  <a href=".">Alan Yuille</a><sup>1</sup>
+</p>
+
+<p align="center">
+  <sup>1</sup> Johns Hopkins University &nbsp;&nbsp;
+  <sup>2</sup> DEVCOM Army Research Laboratory
+</p>
+
+
+<p align="center">
+  <a href="https://xingruiwang.github.io/projects/Spatial457/">Project Page</a> /
+  <a href="https://arxiv.org/abs/2502.08636">Paper</a> /
+  <a href="https://huggingface.co/datasets/RyanWW/Spatial457">🤗 Huggingface</a> /
+  <a href="https://github.com/XingruiWang/Spatial457">Code</a>
+</p>
+
+
+<p align="center">
+  <img src="https://github.com/XingruiWang/Spatial45r/imgs/teaser.png?raw=True" alt="Spatial457 Teaser" width="80%">
+</p>
+
+<!-- <p align="center"><i>
+  Official implementation of the CVPR 2025 (Highlight) paper:  
+  <strong>Spatial457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Multimodal Models</strong>
+</i></p> -->
+
+---
+
+## 🧠 Introduction
+
+Spatial457 is a diagnostic benchmark designed to evaluate the 6D spatial reasoning capabilities of large multimodal models (LMMs). It systematically introduces four key capabilities—multi-object understanding, 2D and 3D localization, and 3D orientation—across five difficulty levels and seven question types, progressing from basic recognition to complex physical interaction.
+
+---
+
+## 📦 Download
+
+You can access the full dataset and evaluation toolkit:
+
+- **Dataset**: [Hugging Face](https://huggingface.co/datasets/RyanWW/Spatial457)  
+- **Code**: [GitHub Repository](https://github.com/XingruiWang/Spatial457)  
+- **Paper**: [arXiv 2502.08636](https://arxiv.org/abs/2502.08636)
+
+---
+
+## 📊 Benchmark
+
+We benchmarked a wide range of state-of-the-art models—including GPT-4o, Gemini, Claude, and several open-source LMMs—on all subsets. Performance consistently drops as task difficulty increases. PO3D-VQA and humans remain most robust across all levels.
+
+The table below summarizes model performance across 7 subsets:
+
+<!-- Include table image or markdown table here if needed -->
+
+---
+
+## 📚 Citation
+
+```bibtex
+@inproceedings{wang2025spatial457,
+  title     = {Spatial457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Multimodal Models},
+  author    = {Wang, Xingrui and Ma, Wufei and Zhang, Tiezheng and de Melo, Celso M and Chen, Jieneng and Yuille, Alan},
+  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+  year      = {2025},
+  url       = {https://arxiv.org/abs/2502.08636}
+}