论文标题
一个简单而通用的旋转模棱两可的点云网络
A Simple and Universal Rotation Equivariant Point-cloud Network
论文作者
论文摘要
对置换和僵化动作的等效性是针对各种3D学习问题的重要归纳偏见。最近，已经显示，等效的张量现场网络体系结构是通用的 - 它可以近似任何模棱两可的函数。在本文中，我们建议一个简单得多的体系结构，证明它享有相同的普遍性并评估其在ModelNet40上的性能。重现我们的实验的代码可在\ url {https://github.com/simpleinvariance/universalnetwork}中获得
Equivariance to permutations and rigid motions is an important inductive bias for various 3D learning problems. Recently it has been shown that the equivariant Tensor Field Network architecture is universal -- it can approximate any equivariant function. In this paper we suggest a much simpler architecture, prove that it enjoys the same universality guarantees and evaluate its performance on Modelnet40. The code to reproduce our experiments is available at \url{https://github.com/simpleinvariance/UniversalNetwork}
