NHO: A Neural Hamiltonian Operator for Anchor-based Region Localization and Dense Correspondence

arXiv:2609.37048 · cs.CV · Submitted 2026-09-29 · Read on arXiv

cs.CV

Submitted: 2026-09-29

Updated: 2026-09-30

Terminology

• Alignment — 17× in this paper · explained in 1 episode
• Accuracy — 9× in this paper · explained in 1 episode
• Robustness — 9× in this paper · explained in 5 episodes
• Consistency — 8× in this paper · explained in 3 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Neural Hamiltonian Operator — 5× in this paper
• ACM Transactions on Graphics — 4× in this paper
• Computer Vision and Pattern Recognition — 3× in this paper
• F1 Score — 3× in this paper · explained in 3 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Agnostic Learning — 1× in this paper · explained in 1 episode
• Anchor Loss — 1× in this paper · explained in 1 episode
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Persistent Homology — 1× in this paper · explained in 3 episodes

Sources

• Partial Shape Similarity via Alignment of Multi-Metric Hamiltonian Spectra
• Hyper-Network Neural Functional Maps for Unsupervised Robust 3D Shape Matching

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