Top-Down Beats Bottom-Up in 3D Instance Segmentation

Understand

Most 3D instance segmentation methods exploit a bottom-up strategy, typically including resource-exhaustive post-processing.

• For point grouping, bottom-up methods rely on prior assumptions about the objects in the form of hyperparameters, which are domain-specific and need to be carefully tuned.
• On the contrary, we address 3D instance segmentation with a TD3D: the pioneering cluster-free, fully-convolutional and entirely data-driven approach trained in an end-to-end manner.
• This is the first top-down method outperforming bottom-up approaches in 3D domain.