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arXiv · 2609.08848

FIRE3D: Feed-forward Interactive 3D Scene Reconstruction Within A Minute

Hongchi Xia·Tianhang Cheng·Wei-Chiu Ma·Shenlong Wang
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Abstract

We present FIRE3D, a unified framework that takes a single RGB image or casual RGB video and transforms it into simulation-ready 3D scene assets for games and interactive applications in under a minute. At the core of FIRE3D is a feed-forward, end-to-end network that predicts a compositional scene representation from posed RGB-D observations estimated from the RGB capture, including the 6-DoF pose, bounding box, mesh, and texture for every object. By modeling the scene as a collection of discrete entities, FIRE3D produces amodally complete and simulation-ready environments where objects are physically decoupled and ready for interaction. Our framework requires no test-time optimization, runs orders of magnitude faster than prior interaction-ready methods, and provides object-level completeness beyond existing feed-forward 3D approaches. We demonstrate competitive or state-of-the-art results across pose accuracy, geometry completeness, and texture quality across various datasets while being orders of magnitudes faster. Project page: https://xiahongchi.github.io/Fire3D/

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Hongchi Xia, Tianhang Cheng, Wei-Chiu Ma, Shenlong Wang. 2026-09-08. FIRE3D: Feed-forward Interactive 3D Scene Reconstruction Within A Minute. https://arxiv.org/abs/2609.08848

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