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README.md

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-  <h1>Spatial Reasoning with Vision-Language Models in Ego-Centric Multi-view Scenes (Code Comes Soon!)</h1>
-  <p><i>Benchmarking and Improving 3D Spatial Reasoning in Vision-Language Models</i></p>
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+  <h1>Spatial Reasoning with Vision-Language Models in Ego-Centric Multi-view Scenes</h1>
 <a href="https://arxiv.org/abs/2509.06266" target="_blank">
     <img alt="arXiv" src="https://img.shields.io/badge/arXiv-red?logo=arxiv" height="20" />
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-![Sample](figs/Fig2_v4.png)
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-### 📌 Key Highlights
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-- 📊 **Ego3D-Bench**: A benchmark of **8,600+ human-verified QA pairs** for evaluating VLMs in **ego-centric, multi-view outdoor environments**.  
-- 🧠 **Ego3D-VLM**: A **post-training framework** that builds cognitive maps from global 3D coordinates, achieving **+12% QA accuracy** and **+56% distance estimation** improvements.  
-- 🚀 **Impact**: Together, Ego3D-Bench and Ego3D-VLM move VLMs closer to **human-level 3D spatial understanding** in real-world settings.  
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-### ⚖️ **Ego3D-Bench**
-Benchmark Overview: We introduce Ego3D-Bench, a benchmark designed to evaluate the spatial understanding of VLMs in ego-centric multi-view scenarios. Images are collected from three different datasets: NuScenes, Argoverse, and Waymo. Questions are designed to require cross-view reseasoning. We define question from the ego-perspective and from the perspective of objects in the scene. To clearly indicate the perspective of each question, we categorize them into ego-centric or object-centric. In total we have 10 questions: 8 multi-choice QAs and 2 exact number QAs. Figure 
+### ⚖️ **Ego3D-Bench Overview**
+We introduce Ego3D-Bench, a benchmark designed to evaluate the spatial understanding of VLMs in ego-centric multi-view scenarios. Images are collected from three different datasets: NuScenes, Argoverse, and Waymo. Questions are designed to require cross-view reseasoning. We define question from the ego-perspective and from the perspective of objects in the scene. To clearly indicate the perspective of each question, we categorize them into ego-centric or object-centric. In total we have 10 questions: 8 multi-choice QAs and 2 exact number QAs. Figure 
 
 ![Sample](figs/Fig5_v2.png)