Research map / Point clouds / Shape and surface completion
Neural Kernel Surface Reconstruction
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use gradient-based energy fitting instead of exact positional interpolation | Neural Kernel Surface Reconstruction · ABC/Thingi10K and ShapeNet reconstruction | reconstruction quality | Helped |
| Remove the gradient-based matrices from the coefficient solve (ablation) | NKSR · Ablation study | IoU | Hurt |
| Remove hierarchy levels from the linear solver (ablation) | NKSR · Ablation study | IoU | Hurt |
| Increase feature dimension for kernel computation (ablation) | NKSR · Ablation study | IoU | Helped |
| Vary voxel size (ablation) | NKSR · Ablation study | IoU | Mixed |
| Train one kitchen-sink model on mixed datasets instead of a domain-specific model | NKSR · ABC/Thingi10K and CARLA | reconstruction quality | Mixed |
| Use a globally supported kernel with exact positional occupancy constraints | NKF · Noisy point-cloud reconstruction | noise robustness | Hurt |
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