Domain-Incremental Learning on CDDB Hard
89.1Accuracy (AT)CoVON
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| CoVONModel=CLIP with pretrained ViT-B/16 as vision encoder2026.06 | 89.1 | — | — | 0.56 | |
| MoP-CLIPModel=CLIP with pretrained ViT-B/16 as vision encoder2026.06 | 88.65 | — | — | 0.69 | |
| DyToxModel=Vision Transformer (ViT-B/16)2026.06 | 86.21 | — | — | 1.55 | |
| S-liPromptsModel=CLIP with pretrained ViT-B/16 as vision encoder2026.06 | 86.08 | — | — | 1.12 | |
| PINAModel=CLIP with pretrained ViT-B/16 as vision encoder2026.06 | 85.71 | — | — | 1.21 | |
| CoVONModel=Vision Transformer (ViT-B/16)2026.06 | 82.24 | — | — | 0.47 | |
| CoVON-NoMModel=Vision Transformer (ViT-B/16)2026.06 | 80.11 | — | — | 0.67 | |
| PINAModel=Vision Transformer (ViT-B/16)2026.06 | 77.35 | — | — | 0.98 | |
| S-iPromptsModel=Vision Transformer (ViT-B/16)2026.06 | 74.51 | — | — | 1.3 | |
| CODA-PModel=Vision Transformer (ViT-B/16)2026.06 | 73.15 | — | — | 0.99 | |
| EWC*Model=Vision Transformer (ViT-B/16)2026.06 | 70.94 | — | — | 1.54 | |
| DualPromptModel=Vision Transformer (ViT-B/16)2026.06 | 64.8 | — | — | 8.74 | |
| L2PModel=Vision Transformer (ViT-B/16)2026.06 | 61.08 | — | — | 9.23 | |
| LwFModel=Vision Transformer (ViT-B/16)2026.06 | 60.94 | — | — | 16.24 | |
| EWCModel=Vision Transformer (ViT-B/16)2026.06 | 50.59 | — | — | 27.62 | |
| CODA-PromptBackbone=ViT-B/16-IN1K, Exemplars=02024.10 | — | 69.19 | 74.18 | — | |
| DualPromptBackbone=ViT-B/16-IN1K, Exemplars=02024.10 | — | 68.33 | 71.41 | — | |
| DUCTBackbone=ViT-B/16-IN1K, Exemplars=02024.10 | — | 84.14 | 85.1 | — | |
| EASEBackbone=ViT-B/16-IN1K, Exemplars=02024.10 | — | 67.78 | 64.96 | — | |
| FinetuneBackbone=ViT-B/16-IN1K, Exemplars=02024.10 | — | 52.08 | 50.11 | — | |
| iCaRLBackbone=ViT-B/16-IN1K, Exemplars=10 per class2024.10 | — | 68.43 | 70.5 | — | |
| L2PBackbone=ViT-B/16-IN1K, Exemplars=02024.10 | — | 67.33 | 64.45 | — | |
| MEMOBackbone=ViT-B/16-IN1K, Exemplars=10 per class2024.10 | — | 60.87 | 58.09 | — | |
| RanPACBackbone=ViT-B/16-IN1K, Exemplars=02024.10 | — | 78.92 | 80.48 | — | |
| ReplayBackbone=ViT-B/16-IN1K, Exemplars=10 per class2024.10 | — | 66.91 | 63.21 | — | |
| S-iPromptBackbone=ViT-B/16-IN1K, Exemplars=02024.10 | — | 68.51 | 72.76 | — | |
| SimpleCILBackbone=ViT-B/16-IN1K, Exemplars=02024.10 | — | 60.8 | 63.4 | — |