We propose LiteReality, a novel pipeline that converts RGB-D scans of indoor environments into compact, realistic, and interactive 3D virtual replicas. LiteReality not only reconstructs scenes that visually resemble reality but also supports key features essential for graphics pipelines -- such as object individuality, articulation, high-quality physically based rendering materials, and physically based interaction. At its core, LiteReality first performs scene understanding and parses the results into a coherent 3D layout and objects with the help of a structured scene graph. It then reconstructs the scene by retrieving the most visually similar 3D artist-crafted models from a curated asset database. Next, the Material Painting module enhances realism by recovering high-quality, spatially varying materials. Finally, the reconstructed scene is integrated into a simulation engine with basic physical properties to enable interactive behavior. The resulting scenes are compact, editable, and fully compatible with standard graphics pipelines, making them suitable for applications in AR/VR, gaming, robotics, and digital twins. In addition, LiteReality introduces a training-free object retrieval module that achieves state-of-the-art similarity performance on the Scan2CAD benchmark, along with a robust material painting module capable of transferring appearances from images of any style to 3D assets -- even under severe misalignment, occlusion, and poor lighting. We demonstrate the effectiveness of LiteReality on both real-life scans and public datasets. Project page: https://litereality.github.io; Video: https://www.youtube.com/watch?v=ecK9m3LXg2c

翻译：我们提出LiteReality——一种将室内环境RGB-D扫描转换为紧凑、逼真且可交互的三维虚拟副本的新型流水线。该方案不仅重建出视觉上接近真实的场景，还支持图形学流水线所需的关键特性，包括物体独立性、关节运动、基于物理的高质量渲染材质及物理交互。其核心流程首先执行场景理解，借助结构化场景图将解析结果组织为一致的三维布局与物体；随后通过从精选资产数据库中检索视觉最相似的三维艺术家创作模型完成场景重建；接着利用材质绘制模块通过恢复高质量空间变化材质增强真实感；最后将重建场景集成至具备基础物理属性的仿真引擎中，实现可交互行为。生成场景具有紧凑性、可编辑性，且与标准图形学流水线完全兼容，适用于增强现实/虚拟现实、游戏、机器人及数字孪生等应用。此外，LiteReality引入无需训练的物体检索模块，在Scan2CAD基准上达到最先进的相似度性能；同时配备鲁棒的材质绘制模块，能够将任意风格的图像外观迁移至三维资产——即使面对严重错位、遮挡及光照不足的情况。我们通过真实扫描场景与公开数据集验证了LiteReality的有效性。项目页面：https://litereality.github.io；视频：https://www.youtube.com/watch?v=ecK9m3LXg2c