论文标题
非水晶网状重建
Nonwatertight Mesh Reconstruction
论文作者
论文摘要
从无调点云中重建3D非紧密网格是计算机视觉和计算机图形的一个未开发的区域。在这个项目中，我们试图通过扩展基于学习的网眼重建管道来解决此问题，该管道在“ Shape As Points”中呈现。我们方法的核心是将问题作为语义分割问题提出，该问题识别了3D体积中的区域，其中网格表面位于所示区域并从检测到的区域提取表面。与基线技术相比，我们的方法取得了令人信服的结果。
Reconstructing 3D non-watertight mesh from an unoriented point cloud is an unexplored area in computer vision and computer graphics. In this project, we tried to tackle this problem by extending the learning-based watertight mesh reconstruction pipeline presented in the paper 'Shape as Points'. The core of our approach is to cast the problem as a semantic segmentation problem that identifies the region in the 3D volume where the mesh surface lies and extracts the surfaces from the detected regions. Our approach achieves compelling results compared to the baseline techniques.
