Sonicmesh: Enhancing 3D Human Mesh Reconstruction in Vision-Impaired Environments With Acoustic Signals

arXiv:2412.11325 · cs.CV, cs.SD, eess.AS · Submitted 2024-12-15 · Read on arXiv

cs.CV, cs.SD, eess.AS

Submitted: 2024-12-15

Updated: 2026-09-25

Terminology

• Transformer — 15× in this paper · explained in 2 episodes
• Accuracy — 12× in this paper · explained in 1 episode
• Alignment — 11× in this paper · explained in 1 episode
• Embeddings — 9× in this paper · explained in 2 episodes
• Registration Module — 8× in this paper
• Conference on Computer Vision and Pattern Recognition — 5× in this paper
• Consistency — 4× in this paper · explained in 3 episodes
• Feature Extraction — 4× in this paper · explained in 2 episodes
• Aperture — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• CVF International Conference on Computer Vision — 3× in this paper
• Global Integrated Module — 3× in this paper
• Robustness — 3× in this paper · explained in 5 episodes
• Synthetic Aperture Radar — 3× in this paper
• Ablation — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• Convolutional Neural Network — 2× in this paper
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Inverse Synthetic Aperture Radar — 2× in this paper
• Radio Frequency — 2× in this paper
• Structural Integrity — 2× in this paper · explained in 3 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Alignment Techniques — 1× in this paper · explained in 1 episode
• Clustering — 1× in this paper · explained in 2 episodes
• D Fast Fourier Transform — 1× in this paper
• D Human Mesh Reconstruction — 1× in this paper
• Gaussian Mixture Model — 1× in this paper
• Gaussian Mixture Model (GMM) — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Multimodal Fusion — 1× in this paper · explained in 3 episodes
• Multimodal Inputs — 1× in this paper · explained in 2 episodes
• Per Vertex Error — 1× in this paper
• Representation Learning — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes

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