评估单视图三维重建在机器人实时仿真中的适用性，发现现有方法仍不达标。
Is Single-View Mesh Reconstruction Ready for Robotics?
- 针对机器人需求设计新评测标准，涵盖几何稳定性与计算效率
- 在真实机器人数据集上验证，多数方法无法生成可用的物理仿真模型
- 揭示计算机视觉进展与机器人实际需求间的显著差距
本文评估单视图网格重建模型在机器人领域的应用潜力，旨在实现基于物理模拟器的实时规划与动力学预测所需的即时数字孪生创建。近期单视图3D重建技术为实现实时物理仿真提供了可能：直接将场景单次观测转化为可模拟的完整、物理合理的3D网格。然而，其在即时性、物理保真度和仿真就绪性方面是否满足机器人应用需求尚不明确。我们建立了面向机器人的专用评测标准，包括对典型输入的处理能力、无碰撞稳定几何结构、遮挡鲁棒性及满足计算约束的能力。在真实机器人数据集上的实证评估表明，尽管现有方法在计算机视觉基准上表现良好，却未能满足机器人特定要求。我们定量分析了单视图重建在实际机器人应用中的局限性，区别于以往聚焦多视角方法的研究。研究结果揭示了计算机视觉进步与机器人实际需求之间的关键差距，为该交叉领域未来研究指明方向。
原文摘要 · Abstract (English)
This paper evaluates single-view mesh reconstruction models for their potential in enabling instant digital twin creation for real-time planning and dynamics prediction using physics simulators for robotic manipulation. Recent single-view 3D reconstruction advances offer a promising avenue toward an automated real-to-sim pipeline: directly mapping a single observation of a scene into a simulation instance by reconstructing scene objects as individual, complete, and physically plausible 3D meshes. However, their suitability for physics simulations and robotics applications under immediacy, physical fidelity, and simulation readiness remains underexplored. We establish robotics-specific benchmarking criteria for 3D reconstruction, including handling typical inputs, collision-free and stable geometry, occlusions robustness, and meeting computational constraints. Our empirical evaluation using realistic robotics datasets shows that despite success on computer vision benchmarks, existing approaches fail to meet robotics-specific requirements. We quantitively examine limitations of single-view reconstruction for practical robotics implementation, in contrast to prior work that focuses on multi-view approaches. Our findings highlight critical gaps between computer vision advances and robotics needs, guiding future research at this intersection.
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