3D Shape Reconstruction on ShapeNet Table
0.029Chamfer DistanceDCC-DIF
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| DCC-DIF2022.03 | 0.029 | 0.993 | — | |
| Multi-scale Deep Implicit Functions2022.03 | 0.046 | 0.976 | — | |
| IF-Net2022.03 | 0.17 | 0.934 | — | |
| Mixing-Denoising Generalizable Occupancy NetworksNumber of points=3000, Noise level (sigma)=0.0052023.11 | 0.3 | 0.99 | 0.96 | |
| Occupancy Networks2022.03 | 0.44 | 0.849 | — | |
| Learned Discrete Implicit Functions2022.03 | 0.56 | 0.924 | — | |
| SA-ConvONetNumber of points=3000, Noise level (sigma)=0.0052023.11 | 0.56 | 0.92 | 0.93 | |
| Neural-PullNumber of points=3000, Noise level (sigma)=0.0052023.11 | 0.71 | 0.83 | 0.85 | |
| Structured Implicit Functions2022.03 | 1.57 | 0.557 | — |