Image Classification on Aircraft, Caltech101, DTD, Flowers, Food, Pets, SUN397
81.9Average AccuracyQUEST
Evaluation Results
| Method | Links | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| QUESTAttention=QUEST, Pre-training=iBOT, Backbone=ViT-B/162026.03 | 81.9 | — | — | — | — | — | — | — | |
| QUESTAttention=QUEST, Pre-training=iBOT-vMF on ImageNet-1K, Evaluation Protocol=Transfer linear probes2026.03 | 81.9 | 59.9 | 95.1 | 74.4 | 95.8 | 83.9 | 94.3 | 69.8 | |
| Standard AttentionAttention=Standard, Pre-training=iBOT, Backbone=ViT-B/162026.03 | 81.5 | — | — | — | — | — | — | — | |
| Standard AttentionAttention=Standard, Pre-training=iBOT-vMF on ImageNet-1K, Evaluation Protocol=Transfer linear probes2026.03 | 81.5 | 58.1 | 95.5 | 74.7 | 94.8 | 83.6 | 93.9 | 70.2 |