Visual Cortex Alignment on Natural Scenes Dataset (NSD) (20% val)
0.245Reconstruction CorrelationPairwise Best OT
Evaluation Results
| Method | Links | |
|---|---|---|
| Pairwise Best OTModel 1=Subject A, Model 2=Subject B2025.10 | 0.245 | |
| MOTModel 1=Subject A, Model 2=Subject B2025.10 | 0.244 | |
| Single-Best OTModel 1=Subject A, Model 2=Subject B2025.10 | 0.244 | |
| MOTModel 1=Subject B, Model 2=Subject C2025.10 | 0.212 | |
| Single-Best OTModel 1=Subject B, Model 2=Subject C2025.10 | 0.212 | |
| Pairwise Best OTModel 1=Subject B, Model 2=Subject C2025.10 | 0.212 | |
| Pairwise Best OTModel 1=Subject B, Model 2=Subject D2025.10 | 0.204 | |
| Pairwise Best OTModel 1=Subject A, Model 2=Subject C2025.10 | 0.202 | |
| Pairwise Best OTModel 1=Subject A, Model 2=Subject D2025.10 | 0.201 | |
| MOTModel 1=Subject B, Model 2=Subject D2025.10 | 0.201 | |
| Single-Best OTModel 1=Subject B, Model 2=Subject D2025.10 | 0.201 | |
| MOTModel 1=Subject A, Model 2=Subject C2025.10 | 0.199 | |
| Single-Best OTModel 1=Subject A, Model 2=Subject C2025.10 | 0.199 | |
| Pairwise Best OTModel 1=Subject C, Model 2=Subject D2025.10 | 0.199 | |
| MOTModel 1=Subject A, Model 2=Subject D2025.10 | 0.198 | |
| Single-Best OTModel 1=Subject A, Model 2=Subject D2025.10 | 0.198 | |
| MOTModel 1=Subject C, Model 2=Subject D2025.10 | 0.197 | |
| Single-Best OTModel 1=Subject C, Model 2=Subject D2025.10 | 0.197 | |
| Random (Perm-P)Model 1=Subject A, Model 2=Subject B2025.10 | 0.135 | |
| Random (Perm-P)Model 1=Subject B, Model 2=Subject C2025.10 | 0.126 | |
| Random (Perm-P)Model 1=Subject B, Model 2=Subject D2025.10 | 0.121 | |
| Random (Perm-P)Model 1=Subject C, Model 2=Subject D2025.10 | 0.112 | |
| Random (Perm-P)Model 1=Subject A, Model 2=Subject C2025.10 | 0.11 | |
| Random (Perm-P)Model 1=Subject A, Model 2=Subject D2025.10 | 0.109 |