Structure-First Point Cloud Learning with Mapper Region Graphs

arXiv:2602.05522 · cs.CV, math.GT · Submitted 2026-02-05 · Read on arXiv

cs.CV, math.GT

Submitted: 2026-02-05

Updated: 2026-09-27

Terminology

• Robustness — 47× in this paper · explained in 5 episodes
• Abstraction — 29× in this paper · explained in 1 episode
• Clustering — 17× in this paper · explained in 2 episodes
• Accuracy — 14× in this paper · explained in 1 episode
• Aggregation — 11× in this paper · explained in 1 episode
• Benchmark — 5× in this paper · explained in 2 episodes
• Graph Isomorphism Network — 5× in this paper
• Graph Neural Networks — 4× in this paper
• Point Clouds — 4× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Corruption Robustness — 3× in this paper · explained in 2 episodes
• Data Augmentation — 3× in this paper · explained in 7 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 3× in this paper
• Graph Construction — 2× in this paper · explained in 3 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adversarial Training — 1× in this paper · explained in 1 episode
• Aggregation Function — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Failure Modes — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• GNNs — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Multi-layer Perceptron — 1× in this paper
• Parameter Efficiency — 1× in this paper · explained in 3 episodes
• Principal Component Analysis (PCA) — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Topological Data Analysis (TDA) — 1× in this paper · explained in 2 episodes

Sources

• PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

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