Office-Caltech
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | Office-Caltech-10 (test) | Average Accuracy98.65 | 58 | |
| Image Classification | Office-Caltech | Average Accuracy0.989 | 44 | |
| Image Classification | Office-Caltech (test) | Average Accuracy95.8 | 35 | |
| Multi-Target Domain Adaptation | Office-Caltech | Acc (A -> C,D,W)96.1 | 21 | |
| Multi-task Classification | Office-Caltech | Accuracy (Task o)98.61 | 20 | |
| Image Classification | Office-Caltech10 | Class A Accuracy97.93 | 18 | |
| Image Classification | Office-Caltech10 (unseen clients) | Accuracy (C)0.88 | 14 | |
| Multi-source closed-set UDA | Office-Caltech target domains A, C, D, W | Acc (Target A)0.968 | 13 | |
| Multi-source Unsupervised Domain Adaptation | Office-Caltech multi-source ResNet-101 | Accuracy (→A)96.7 | 13 | |
| Unsupervised Multi-Source Domain Adaptation | Office-Caltech10 | Accuracy (Amazon)99.7 | 12 | |
| Object Recognition | Office-Caltech | Accuracy (Amazon)97.38 | 12 | |
| Federated Image Classification | Office-Caltech | Accuracy (Caltech)64.61 | 9 | |
| Image Classification | Office-Caltech Multi-source | Accuracy (R -> A)96.4 | 9 | |
| Federated Learning Image Classification | Office-Caltech10 (test) | Amazon Accuracy19.5 | 8 | |
| Image Classification | Office-Caltech Multi-target | Accuracy (A -> R)96.2 | 8 | |
| Object Recognition | Office-Caltech10 SURF features various domain shifts | Acc (A->C)40.3 | 7 | |
| Image Classification | Office-Caltech10 Feature & Label Shifts (alpha=0.1) (test) | Metric- | 0 |
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