# Cut a Wall, See a Wall: Identity Substitution in Occluded Point-Cloud Perception for Construction Robots

- Source: arXiv cs.RO
- Published: 2026-10-27T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/capr0e704ujb4dqxp9rcxxeqx
- Original: https://arxiv.org/abs/2610.34040

## Summary

The paper finds that when entire regions of a scene are occluded at test time, point-cloud segmentation networks relabel the hidden elements into a single sink class; under fixed layouts this class absorbs up to 70% of test points, and baseline mIoU drops to 0.15-0.27. The authors append 14 hand-computed geometric features per point (GPE), restoring mIoU to 0.54-0.92 on PointNet++ and a PTv3-style transformer and removing 64-100% of whole-object losses; on real S3DIS scans, whole-wall losses drop from 10 to 0.