Golf Motion Interpolation Model Performance

GAT vs Pure Hierarchical Architecture Comparison

Best Performing Models (GAT Architecture)

0.2595
Best MPJPE (mm)
HierGAT_7h8_g2
0.2106
Best P-MPJPE (mm)
HierGAT_7h8_g2
99.75%
Best OKS mAP
HierGAT_7h8_g2
100%
PCK@150mm
All Models
Main Performance Metrics Comparison
Error Analysis with Standard Deviation
OKS AP Performance by Threshold
GAT vs Pure Hierarchical Architecture
Model Architecture Complexity Comparison
Transformer Configuration Impact

Model Architecture Comparison

🏗️ GAT Architecture (Enhanced)

  • Multi-layer GAT: 3 hierarchical GAT layers with residual connections
  • Advanced Attention: 3 cross-attention layers for feature fusion
  • Global Residual: Skip connections across all layers
  • Multi-block Prediction: 3 prediction blocks with residual
  • Feature Integration: Concatenation of all intermediate features
  • Complexity: High computational cost, better performance

🏛️ Pure Hierarchical (Base)

  • Single GCN: One hierarchical GCN layer
  • Simple Attention: Single cross-attention layer
  • Basic Residual: Standard residual connections
  • Single Prediction: One prediction head
  • Direct Processing: Sequential feature processing
  • Complexity: Lower computational cost, good baseline

🔍 Key Architectural Differences

Graph Processing

GAT: Graph Attention with learnable edge weights
GCN: Fixed graph convolution

Feature Flow

GAT: Multi-path with global fusion
GCN: Single-path sequential

Performance

GAT: 27% better MPJPE
GCN: Faster inference

Model Architecture MPJPE (mm) P-MPJPE (mm) OKS mAP (%) [email protected] [email protected] Std Dev

🚀 Performance Analysis & Recommendations

📊 Quantitative Findings

  • GAT Advantage: 27% better MPJPE performance
  • Attention Impact: Multi-head configurations show clear benefits
  • Consistency: GAT models have lower standard deviation
  • OKS Excellence: All models achieve >99.4% mAP

🎯 Deployment Recommendations

  • Production: HierGAT_7h8_g2 for best accuracy
  • Real-time: Hier_7h16 for speed-accuracy balance
  • Mobile: Consider Hier_8h8 for resource constraints
  • Research: Explore GAT head optimization (1-3 range)