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## 🔍 Abstract
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**RoboTransfer** is a novel diffusion-based video generation framework tailored for robotic visual policy transfer. Unlike conventional approaches, RoboTransfer introduces **geometry-aware synthesis** by injecting **depth and normal priors**, ensuring multi-view consistency across dynamic robotic scenes. The method further supports **explicit control over scene components**, such as **background editing**, **object identity swapping**, and **motion specification**, offering a fine-grained video generation pipeline that benefits embodied learning.
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## 📸 Framework Overview
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> The overall architecture includes view-specific encoding, geometry injection, diffusion denoising with spatial constraints, and component-level editing modules. Our system enables compositional control over scene dynamics while preserving physical and geometric consistency.
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## 📖 BibTeX
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```bibtex
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<img src="assets/pin.jpeg" width="50%" alt="RoboTransfer"/></div>
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## 🔍 Abstract
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**RoboTransfer** is a novel diffusion-based video generation framework tailored for robotic visual policy transfer. Unlike conventional approaches, RoboTransfer introduces **geometry-aware synthesis** by injecting **depth and normal priors**, ensuring multi-view consistency across dynamic robotic scenes. The method further supports **explicit control over scene components**, such as **background editing**, **object identity swapping**, and **motion specification**, offering a fine-grained video generation pipeline that benefits embodied learning.
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## 📖 BibTeX
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```bibtex
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