This paper proposes a novel block merging algorithm suitable for any block-based 3D instance segmentation technique. The proposed work improves over the state-of-the-art by allowing wrongly labelled points of already processed blocks to be corrected through label propagation. By doing so, instance overlap between blocks is not anymore necessary to produce the desirable results, which is the main limitation of the current art. Our experiments show that the proposed block merging algorithm significantly and consistently improves the obtained accuracy for all evaluation metrics employed in literature, regardless of the underlying network architecture.

翻译：本文提出一种适用于任何基于块的三维实例分割技术的新型块合并算法。该工作通过允许已处理块中错误标记的点通过标签传播进行校正，从而改进了现有技术。通过这种方式，不再需要块之间的实例重叠来产生理想结果，而这正是当前技术的主要局限。我们的实验表明，无论底层网络架构如何，所提出的块合并算法在所有文献采用的评估指标上均能显著且持续地提升所得精度。