SpaCeFormer delivers 11.1 zero-shot mAP on ScanNet200 (2.8x prior proposal-free best) and runs 2-3 orders of magnitude faster than multi-stage 2D+3D pipelines by using spatial window attention and Morton-curve serialization to predict instance masks from learned queries.
Matterport3d: Learning from rgb-d data in indoor environments
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SpaCeFormer: Fast Proposal-Free Open-Vocabulary 3D Instance Segmentation
SpaCeFormer delivers 11.1 zero-shot mAP on ScanNet200 (2.8x prior proposal-free best) and runs 2-3 orders of magnitude faster than multi-stage 2D+3D pipelines by using spatial window attention and Morton-curve serialization to predict instance masks from learned queries.