Point Cloud Generation on ShapeNet Chair
83.691-NNA (CD)r-GAN
Evaluation results
| Method | Links | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| r-GAN2023.07 | 83.69 | — | — | — | — | 99.7 | 24.27 | 15.13 | |
| GET3D2023.07 | 75.26 | — | — | — | — | 72.49 | 43.36 | 42.77 | |
| l-GANOptimization Metric=EMD2023.07 | 71.9 | — | — | — | — | 64.65 | 38.07 | 44.86 | |
| ShapeGFSampling Time (s)=0.342022.12 | 68.96 | — | — | — | — | 65.48 | — | — | |
| 1-GANSampling Time (s)=0.032022.12 | 68.58 | — | — | — | — | 83.84 | — | — | |
| l-GANOptimization Metric=CD2023.07 | 68.58 | — | — | — | — | 83.84 | 41.99 | 29.31 | |
| PointFlowSampling Time (s)=0.272022.12 | 62.84 | — | — | — | — | 60.57 | — | — | |
| PointFlow2023.07 | 62.84 | — | — | — | — | 60.57 | 42.9 | 50 | |
| DPF-NetSampling Time (s)=0.332022.12 | 62 | — | — | — | — | 58.53 | — | — | |
| DPF-Net2023.07 | 62 | — | — | — | — | 58.53 | 44.71 | 48.79 | |
| PVD-DDIMSampling Time (s)=3.15, Sampling steps (N)=1002022.12 | 61.54 | — | — | — | — | 57.73 | — | — | |
| DPMSampling Time (s)=22.82022.12 | 60.05 | — | — | — | — | 74.77 | — | — | |
| DPM2023.07 | 60.05 | — | — | — | — | 74.77 | 44.86 | 35.5 | |
| SoftFlowSampling Time (s)=0.122022.12 | 59.21 | — | — | — | — | 60.05 | — | — | |
| SoftFlow2023.07 | 59.21 | — | — | — | — | 60.05 | 41.39 | 47.43 | |
| PSFSampling Time (s)=0.042022.12 | 58.92 | — | — | — | — | 54.45 | — | — | |
| SetVAE2023.07 | 58.84 | — | — | — | — | 60.57 | 46.83 | 44.26 | |
| SetVAESampling Time (s)=0.032022.12 | 58.76 | — | — | — | — | 61.48 | — | — | |
| PVD2023.07 | 57.09 | — | — | — | — | 60.87 | 36.68 | 49.24 | |
| PVDSampling Time (s)=29.9, Sampling steps (N)=10002022.12 | 56.26 | — | — | — | — | 53.32 | — | — | |
| LION2023.07 | 53.7 | — | — | — | — | 52.34 | 48.94 | 52.11 | |
| MeshDiffusion2023.07 | 53.69 | — | — | — | — | 57.63 | 46 | 46.71 | |
| DiT-3D2023.07 | 49.11 | — | — | — | — | 50.73 | 52.45 | 54.32 | |
| 3D-LDMRepresentation Type=Continuous representation, Domain Specificity=Domain-specific2024.01 | — | 1.68 | 42.6 | — | — | — | — | — | |
| DDMIRepresentation Type=Continuous representation, Domain Specificity=Domain-agnostic2024.01 | — | 1.5 | 51 | — | — | — | — | — | |
| DPM2022.09 | — | 12.276 | 48.94 | 60.11 | 7.797 | — | — | — | |
| DPM3DRepresentation Type=Discrete representation, Training dataset=Acronym2024.01 | — | 1.3 | 56.7 | — | — | — | — | — | |
| FHDM2022.09 | — | 6.644 | 49.5 | 56.87 | 5.913 | — | — | — | |
| GASPRepresentation Type=Continuous representation, Domain Specificity=Domain-agnostic2024.01 | — | 2.5 | 35.3 | — | — | — | — | — | |
| GCN-GAN2022.09 | — | 15.354 | 39.84 | 77.86 | 21.71 | — | — | — | |
| HyperDiffusionRepresentation Type=Continuous representation, Domain Specificity=Domain-specific2024.01 | — | 7.1 | 53 | — | — | — | — | — | |
| PC-GAN2022.09 | — | 13.436 | 46.23 | 69.67 | 6.649 | — | — | — | |
| PointFlow2022.09 | — | 13.631 | 41.86 | 66.13 | 12.47 | — | — | — | |
| PVDRepresentation Type=Discrete representation2024.01 | — | 6.8 | 42.1 | — | — | — | — | — | |
| SDF-DiffusionRepresentation Type=Continuous representation, Domain Specificity=Domain-specific2024.01 | — | 8 | 49.8 | — | — | — | — | — | |
| SDF-StyleGANRepresentation Type=Continuous representation, Domain Specificity=Domain-specific2024.01 | — | 1.9 | 41.1 | — | — | — | — | — | |
| ShapeGF2022.09 | — | 13.175 | 48.53 | 56.17 | 5.996 | — | — | — | |
| Tree-GAN2022.09 | — | 14.936 | 38.02 | 74.92 | 13.28 | — | — | — |