Few-shot 3D Point Cloud Semantic Segmentation
2 papers with code • 1 benchmarks • 1 datasets
S3DIS
Most implemented papers
Few-shot 3D Point Cloud Semantic Segmentation
These fully supervised approaches heavily rely on large amounts of labeled training data that are difficult to obtain and cannot segment new classes after training.
Rethinking Few-shot 3D Point Cloud Semantic Segmentation
zhaochongan/coseg
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CVPR 2024
The former arises from non-uniform point sampling, allowing models to distinguish the density disparities between foreground and background for easier segmentation.
