Object Recognition on N-Caltech101 1.0 (test)
96.47Top-1 AccuracyGEP
Evaluation results
| Method | Links | ||
|---|---|---|---|
| GEPBackbone=ViT-B/16, Pre-training Dataset=Event-1.8M, Ep.=242026.03 | 96.47 | 99.56 | |
| EventBindBackbone=ViT-B/16, Pre-training Dataset=N-ImageNet, Ep.=N/A2026.03 | 94.08 | — | |
| GEPBackbone=ViT-S/16, Pre-training Dataset=Event-1.8M, Ep.=242026.03 | 93.05 | 98.57 | |
| DINOv2Backbone=ViT-S/16, Pre-training Dataset=LVD-142M, Ep.=N/A2026.03 | 91.94 | 98.12 | |
| ECDPBackbone=ViT-S/16, Pre-training Dataset=N-ImageNet, Ep.=3002026.03 | 87.66 | — | |
| MoCo-v3Backbone=ViT-S/16, Pre-training Dataset=ImageNet-1K, Ep.=3002026.03 | 76.59 | — | |
| MAEBackbone=ViT-B/16, Pre-training Dataset=ImageNet-1K, Ep.=8002026.03 | 67.68 | — | |
| ViTBackbone=ViT-S/16, Pre-training Dataset=N-ImageNet, Ep.=3002026.03 | 55.63 | — | |
| BeiTBackbone=ViT-B/16, Pre-training Dataset=ImageNet-1K, Ep.=8002026.03 | 53.1 | — |