This paper introduces 3DFIRES, a novel system for scene-level 3D reconstruction from posed images. Designed to work with as few as one view, 3DFIRES reconstructs the complete geometry of unseen scenes, including hidden surfaces. With multiple view inputs, our method produces full reconstruction within all camera frustums. A key feature of our approach is the fusion of multi-view information at the feature level, enabling the production of coherent and comprehensive 3D reconstruction. We train our system on non-watertight scans from large-scale real scene dataset. We show it matches the efficacy of single-view reconstruction methods with only one input and surpasses existing techniques in both quantitative and qualitative measures for sparse-view 3D reconstruction.

翻译：摘要：本文提出3DFIRES，一种基于有姿态图像进行场景级三维重建的新型系统。该系统设计为仅需单张视图即可工作，能够重建未见场景的完整几何结构，包括隐藏表面。当输入多张视图时，我们的方法可生成所有相机视锥内的完整重建。该方法的核心特点是在特征层级融合多视图信息，从而生成连贯且全面的三维重建。我们在大规模真实场景数据集上的非水密扫描数据上训练系统。实验表明，该方法在仅输入单张图像时能达到与单视图重建方法相当的效果，并在稀疏视图三维重建的定量与定性评估中均超越现有技术。