Geodesic Distance Prediction on ShapeNet refined subset (test)
0.25MRE (%)DGG
Evaluation results
| Method | Links | ||
|---|---|---|---|
| DGGInput=Mesh, Time (s)=37.82026.06 | 0.25 | 0.27 | |
| NeuroGFInput=Points, Time (s)=600, Training duration=Long [L] (10 minutes), Training mode=Per-scene overfitting2026.06 | 0.52 | 0.48 | |
| NeuroGFInput=Points, Time (s)=120, Training duration=Medium [M] (2 minutes), Training mode=Per-scene overfitting2026.06 | 1.84 | 1.69 | |
| FPGDCInput=Mesh, Time (s)=12.12026.06 | 2.49 | 2.31 | |
| HMInput=Mesh, Time (s)=79.72026.06 | 2.52 | 2.71 | |
| NeuroGFInput=Points, Time (s)=60, Training duration=Short [S] (1 minute), Training mode=Per-scene overfitting2026.06 | 3.12 | 2.93 | |
| PRISMInput=Points, Time (s)=0.52026.06 | 3.87 | 2.75 | |
| GeGNNInput=Mesh, Time (s)=18.9, Evaluation protocol=[R] Remeshed testing data2026.06 | 4.43 | 3.26 | |
| EEMInput=Mesh, Time (s)=45.72026.06 | 8.73 | 8.41 | |
| LiteGETime (s)=0.32026.06 | 10.81 | 3.91 | |
| GeGNNInput=Mesh, Time (s)=1.4, Evaluation protocol=[O] Original testing data2026.06 | 23.2 | 20.8 |