A topology-aware self-supervised framework improves unsupervised simulation-to-reality point cloud classification by combining Fourier-encoded global structure, local implicit fields, and contrastive self-training.
Domain adaptive lidar point cloud segmentation with 3d spatial consistency,
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Topology-Aware Modeling for Unsupervised Simulation-to-Reality Point Cloud Recognition
A topology-aware self-supervised framework improves unsupervised simulation-to-reality point cloud classification by combining Fourier-encoded global structure, local implicit fields, and contrastive self-training.