Mantis is the first Mamba-native PEFT framework for 3D point cloud models, using state-aware adapters and dual-serialization distillation to match performance with only 5% trainable parameters.
Sarma, Michael M
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DDS combines multi-granularity distillation from projected 2D features with graph diffusion on superpoints to deliver region-consistent semantic labels for 3D scenes without any dense annotations.
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Mantis: Mamba-native Tuning is Efficient for 3D Point Cloud Foundation Models
Mantis is the first Mamba-native PEFT framework for 3D point cloud models, using state-aware adapters and dual-serialization distillation to match performance with only 5% trainable parameters.
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Distill, Diffuse, and Semanticize (DDS): Annotation-Free 3D Scene Understanding Based on Multi-Granularity Distillation and Graph-Diffusion-Based Segmentation
DDS combines multi-granularity distillation from projected 2D features with graph diffusion on superpoints to deliver region-consistent semantic labels for 3D scenes without any dense annotations.