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README.md

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 ## 📌 Overview
 
 While recent progress in AI and computer vision has been remarkable, there remains a major gap in evaluating causal reasoning over complex visual inputs. **Causal3D** bridges this gap by providing:
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 - **19 curated 3D-scene datasets** simulating diverse real-world causal phenomena.
 - Paired **tabular causal graphs** and **image observations** across multiple views and backgrounds.
 - Benchmarks for evaluating models in both **structured** (tabular) and **unstructured** (image) modalities.
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-## 🧩 Dataset Structure
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-Each sub-dataset (scene) contains:
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-- `images/`: Rendered images under different camera views and backgrounds.
-- `tabular.csv`: Instance-level annotations including object attributes in causal graph.
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 ## 🎯 Evaluation Tasks