TL;DR本文介绍了一个新颖的任务：一对 3D 几何形状配合，并提出了神经形状配合（NSM）来解决此问题。通过关注形状对齐而不是语义线索，我们可以实现跨类别的泛化，NSM 可以在不同设置下有效地运作，并且通过自我监督数据收集流水线进行训练。
Abstract
Learning to autonomously assemble shapes is a crucial skill for many robotic applications. While the majority of existing part assembly methods focus on correctly posing semantic parts to recreate a whole object, we interpret assembly more literally: as mating geometric parts together to achieve a snug fit. By focusing on →