Image Classification on Dogs
86AccuracyCapPa L/14
Evaluation Results
| Method | Links | |
|---|---|---|
| CapPa L/14MAP head=true, Grain=Fine, Frozen representation=true, backbone=ViT-L/142023.06 | 86 | |
| IndividualBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=12024.05 | 85.16 | |
| CLIP* L/14MAP head=true, Grain=Fine, Frozen representation=true, backbone=ViT-L/142023.06 | 85 | |
| EMR-MERGINGBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 81.89 | |
| CapPaMAP head=true, Grain=Fine, Frozen representation=true2023.06 | 81.2 | |
| DREAMWay=5, Shot=52026.03 | 81.2 | |
| CapMAP head=true, Grain=Fine, Frozen representation=true2023.06 | 79.6 | |
| CLIPWay=5, Shot=52026.03 | 78.2 | |
| CLIP* (16k)MAP head=true, Grain=Fine, Frozen representation=true2023.06 | 77.9 | |
| CLIP* (8k)MAP head=true, Grain=Fine, Frozen representation=true2023.06 | 77.5 | |
| SCPTBackbone=ViT-B/322026.07 | 73.13 | |
| ATPromptBackbone=ViT-B/322026.07 | 71.3 | |
| SCPTBackbone=RN502026.07 | 70.63 | |
| CoOpBackbone=ViT-B/322026.07 | 70.23 | |
| FiGKDTeacher=ResNet32x4, Student=ShuffleNet-V22025.05 | 70.14 | |
| MLKDTeacher=ResNet32x4, Student=ShuffleNet-V22025.05 | 69.54 | |
| TCPBackbone=ViT-B/322026.07 | 68.67 | |
| FiGKDTeacher=WRN-40-2, Student=WRN-16-22025.05 | 68.53 | |
| FiGKDTeacher=WRN-40-2, Student=WRN-40-12025.05 | 68.48 | |
| SSPStudent Model=LCNet-35, Teacher Selection Metric=SSP2026.05 | 68 | |
| R12Student Model=LCNet-35, Teacher Selection Metric=R122026.05 | 68 | |
| DKDTeacher=ResNet32x4, Student=ShuffleNet-V22025.05 | 67.97 | |
| TeacherTeacher=ResNet32x42025.05 | 67.79 | |
| MLKDTeacher=WRN-40-2, Student=WRN-40-12025.05 | 67.61 | |
| MLKDTeacher=WRN-40-2, Student=WRN-16-22025.05 | 67.5 | |
| FiGKDTeacher=ResNet32x4, Student=ResNet8x42025.05 | 67.27 | |
| ATPromptBackbone=RN502026.07 | 67.27 | |
| KgCoOpBackbone=ViT-B/322026.07 | 67.13 | |
| MLKDTeacher=ResNet32x4, Student=ResNet8x42025.05 | 67.07 | |
| KDTeacher=WRN-40-2, Student=WRN-16-22025.05 | 67.07 | |
| KDTeacher=WRN-40-2, Student=WRN-40-12025.05 | 67.03 | |
| CoOpBackbone=RN502026.07 | 67.01 | |
| DKDTeacher=WRN-40-2, Student=WRN-16-22025.05 | 66.96 | |
| X+OS_SimCorep=5%2023.03 | 66.82 | |
| DKDTeacher=WRN-40-2, Student=WRN-40-12025.05 | 66.51 | |
| X+OS_SimCoreCriterion=Stopping Criterion2023.03 | 66.48 | |
| KDTeacher=ResNet32x4, Student=ShuffleNet-V22025.05 | 66.37 | |
| DKDTeacher=ResNet32x4, Student=ResNet8x42025.05 | 66.23 | |
| TCPBackbone=RN502026.07 | 66.16 | |
| TeacherTeacher=WRN-40-22025.05 | 65.64 | |
| KgCoOpBackbone=RN502026.07 | 63.63 | |
| KDTeacher=ResNet32x4, Student=ResNet8x42025.05 | 63.43 | |
| FiGKDTeacher=VGG13, Student=VGG82025.05 | 63.41 | |
| StudentStudent=WRN-40-12025.05 | 62.64 | |
| MLKDTeacher=VGG13, Student=VGG82025.05 | 62.58 | |
| StudentStudent=WRN-16-22025.05 | 62.51 | |
| DKDTeacher=VGG13, Student=VGG82025.05 | 61.98 | |
| FiGKDTeacher=WRN-40-2, Student=ShuffleNet-V12025.05 | 61.93 | |
| FiGKDTeacher=ResNet32x4, Student=ShuffleNet-V12025.05 | 61.32 | |
| FiGKDTeacher=VGG13, Student=MobileNet-V22025.05 | 61 | |
| MLKDTeacher=WRN-40-2, Student=ShuffleNet-V12025.05 | 60.9 | |
| MLKDTeacher=VGG13, Student=MobileNet-V22025.05 | 60.56 | |
| TeacherTeacher=VGG132025.05 | 60.55 | |
| KDTeacher=VGG13, Student=VGG82025.05 | 60.33 | |
| DKDTeacher=WRN-40-2, Student=ShuffleNet-V12025.05 | 59.66 | |
| DKDTeacher=VGG13, Student=MobileNet-V22025.05 | 59.57 | |
| CLIPBackbone=ViT-B/322026.07 | 59.35 | |
| StudentStudent=ResNet8x42025.05 | 58.62 | |
| DKDTeacher=ResNet32x4, Student=ShuffleNet-V12025.05 | 58.62 | |
| MLKDTeacher=ResNet32x4, Student=ShuffleNet-V12025.05 | 57.57 | |
| StudentStudent=ShuffleNet-V22025.05 | 57.26 | |
| KDTeacher=VGG13, Student=MobileNet-V22025.05 | 57.26 | |
| ProTextBackbone=ViT-B/322026.07 | 57.17 | |
| KDTeacher=WRN-40-2, Student=ShuffleNet-V12025.05 | 56.7 | |
| CLIPBackbone=RN502026.07 | 55.9 | |
| TACStudent Model=LCNet-35, Teacher Selection Metric=TAC2026.05 | 55.2 | |
| CoCoOpBackbone=ViT-B/322026.07 | 55.07 | |
| KDTeacher=ResNet32x4, Student=ShuffleNet-V12025.05 | 53.75 | |
| StudentStudent=VGG82025.05 | 53.34 | |
| AdaMergingBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 53.09 | |
| CoCoOpBackbone=RN502026.07 | 50.83 | |
| REPAWay=5, Shot=52026.03 | 50.2 | |
| X2023.03 | 49.88 | |
| ProTextBackbone=RN502026.07 | 49.08 | |
| Weight AveragingBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 47.8 | |
| Task ArithmeticBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 47.65 | |
| StudentStudent=MobileNet-V22025.05 | 46.14 | |
| CEStudent Model=LCNet-35, Teacher Selection Metric=None (Cross-Entropy)2026.05 | 43.9 | |
| RegMeanBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 42.89 | |
| StudentStudent=ShuffleNet-V12025.05 | 39.4 | |
| FLUIDWay=5, Shot=52026.03 | 38.9 | |
| MARWay=5, Shot=52026.03 | 37.7 | |
| MGD3+EVLFBackbone=ConvNet-4, Pre-training Dataset=distilled ImageNet-1K subset (0.8x), Evaluation Protocol=Fine-tuning2026.03 | 36.18 | |
| KRR-STBackbone=ConvNet-4, Pre-training Dataset=distilled ImageNet-1K subset (0.8x), Evaluation Protocol=Fine-tuning2026.03 | 35.51 | |
| Ties-MergingBackbone=ViT-B/16, Pre-trained=ImageNet-21k, Number of Merged Models=302024.05 | 26.03 | |
| w/o preBackbone=ConvNet-4, Evaluation Protocol=Fine-tuning2026.03 | 24.59 | |
| RandomBackbone=ConvNet-4, Evaluation Protocol=Fine-tuning2026.03 | 23.08 | |
| FRePoBackbone=ConvNet-4, Pre-training Dataset=distilled ImageNet-1K subset (0.8x), Evaluation Protocol=Fine-tuning2026.03 | 22.05 |