Hierarchical Frequency-Domain Compression of Implicit Geometric Representations for Large-Scale Point Clouds

arXiv:2609.32789 · cs.CV · Submitted 2026-09-26 · Read on arXiv

cs.CV

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Point Clouds — 11× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Reconstruction Error — 4× in this paper · explained in 2 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Activation Function — 2× in this paper · explained in 1 episode
• Unified Framework — 2× in this paper · explained in 5 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Frequency-Domain Analysis — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• LINR-PCGC: Lossless Implicit Neural Representations for Point Cloud Geometry Compression
• Efficient Implicit Neural Compression of Point Clouds via Learnable Activation in Latent Space

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