MaskLRF: Rotation-Invariant Self-Supervised Pretraining for 3D Point Set Analysis

MaskLRF introduces a novel rotation-invariant self-supervised pretraining framework for analyzing 3D point sets, enhancing latent features through masked autoencoding within Local Reference Frames. The approach ensures robustness against inconsistent orientations in real-world applications.