Preprint
Aug 2026
Emergent 3D Instance Segmentation from Self-Supervised Point Transformers
This work investigates whether a frozen, self-supervised point transformer already contains the structural information required to isolate object instances without any handcrafted geometric prior, and develops a training-free segmenter that groups points via connected components on a key-similarity graph, using neither density-based clustering nor proximity priors.
Ted Lentsch, Santiago Montiel-Mar'in, Holger Caesar et al.
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