跨海拔的无约束大规模3D重建与渲染
Unconstrained Large-scale 3D Reconstruction and Rendering across Altitudes
AI总结：
针对灾难救援等场景中因图像有限、无位姿相机和跨海拔极端视角差异导致3D建模困难的问题，开发了首个基于多类相机的3D重建与新视图合成公共基准数据集，并评估了现有方法的基线性能。
摘要：
制作逼真且可导航的3D场地模型需要大量精心采集的图像，这些图像往往是灾难救援或执法一线人员无法获取的。现实挑战包括图像数量有限、异构无位姿相机、光照不一致，以及从不同海拔采集图像时存在的极端视角差异。为推动针对这些挑战的研究，我们开发了首个基于多个已标定地面级、安防级和机载相机的3D重建与新视图合成公共基准数据集。我们展示了包含现实挑战的数据集，独立评估了无位姿相机的标定和渲染新视图的质量，使用最新先进方法演示了基线性能，并指出了未来研究的挑战。
英文摘要：
Production of photorealistic, navigable 3D site models requires a large volume of carefully collected images that are often unavailable to first responders for disaster relief or law enforcement. Real-world challenges include limited numbers of images, heterogeneous unposed cameras, inconsistent lighting, and extreme viewpoint differences for images collected from varying altitudes. To promote research aimed at addressing these challenges, we have developed the first public benchmark dataset for 3D reconstruction and novel view synthesis based on multiple calibrated ground-level, security-level, and airborne cameras. We present datasets that pose real-world challenges, independently evaluate calibration of unposed cameras and quality of novel rendered views, demonstrate baseline performance using recent state-of-practice methods, and identify challenges for further research.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
