ALTO：隐式三维重建的交替潜在拓扑
ALTO: Alternating Latent Topologies for Implicit 3D Reconstruction
摘要：
这项工作介绍了交替潜在的拓扑结构（ALTO）的高保真重建隐式三维表面从嘈杂的点云。以前的工作表明，潜在编码的空间排列对恢复细节很重要。一种思想流派是为每个点编码一个潜在向量（点潜在向量）。另一种思想流派是将点潜伏体投影到网格（网格潜伏体）中，该网格可以是体素网格或三平面网格。每一种思想流派都有取舍。栅格潜在项粗糙，丢失高频细节。相比之下，点潜伏体保留细节。然而，点潜伏期更难以解码成表面，并且质量和运行时间受到影响。在本文中，我们提出ALTO顺序交替几何表示，收敛到一个易于解码的潜在。我们发现，这保留了空间的表现力，使解码轻量级。我们验证ALTO隐式3D恢复，并观察到不仅是一个最先进的性能提高，但3-10 $\times$的运行时间改善。项目网站：https://visual.ee.ucla.edu/alto.htm/。
英文摘要：
This work introduces alternating latent topologies (ALTO) for high-fidelity reconstruction of implicit 3D surfaces from noisy point clouds. Previous work identifies that the spatial arrangement of latent encodings is important to recover detail. One school of thought is to encode a latent vector for each point (point latents). Another school of thought is to project point latents into a grid (grid latents) which could be a voxel grid or triplane grid. Each school of thought has tradeoffs. Grid latents are coarse and lose high-frequency detail. In contrast, point latents preserve detail. However, point latents are more difficult to decode into a surface, and quality and runtime suffer. In this paper, we propose ALTO to sequentially alternate between geometric representations, before converging to an easy-to-decode latent. We find that this preserves spatial expressiveness and makes decoding lightweight. We validate ALTO on implicit 3D recovery and observe not only a performance improvement over the state-of-the-art, but a runtime improvement of 3-10$\times$. Project website at https://visual.ee.ucla.edu/alto.htm/.
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。
