AI RESEARCH
Deformation-based In-Context Learning for Point Cloud Understanding
arXiv CS.CV
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ArXi:2604.02845v1 Announce Type: new Recent advances in point cloud In-Context Learning (ICL) have nstrated strong multitask capabilities. Existing approaches typically adopt a Masked Point Modeling (MPM)-based paradigm for point cloud ICL. However, MPM-based methods directly predict the target point cloud from masked tokens without leveraging geometric priors, requiring the model to infer spatial structure and geometric details solely from token-level correlations via transformers. Additionally, these methods suffer from a