Wasserstein Distance Approximation on ShapeNet V2
0.95R^2RG-se
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| RG-seTraining set size=100, Constraint status=unconstrained2025.09 | 0.95 | 9.9 | 7.8 | |
| RG-seoTraining set size=100, Constraint status=unconstrained2025.09 | 0.95 | 9.8 | 7.8 | |
| RG-sTraining set size=100, Constraint status=unconstrained2025.09 | 0.94 | 1.1 | 8.2 | |
| RG-seTraining set size=100, Constraint status=constrained2025.09 | 0.92 | 1.4 | 9.3 | |
| RG-eTraining set size=100, Constraint status=unconstrained2025.09 | 0.92 | 1.5 | 9.8 | |
| RG-seoTraining set size=100, Constraint status=constrained2025.09 | 0.91 | 1.7 | 1 | |
| RG-eTraining set size=100, Constraint status=constrained2025.09 | 0.9 | 1.7 | 1 | |
| RG-sTraining set size=100, Constraint status=constrained2025.09 | 0.88 | 2 | 1.1 | |
| RG-oTraining set size=100, Constraint status=unconstrained2025.09 | 0.75 | 3.8 | 1.6 | |
| RG-oTraining set size=100, Constraint status=constrained2025.09 | 0.66 | 5.2 | 1.8 | |
| WormholeTraining set size=1002025.09 | 0.65 | 6.6 | 1.8 |