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ResearchFormerly WizWand

Image Classification on ImageNet-Sketch (Target)

50.3AccuracyTAC
15.04424.19733.3542.503Mar 10, 2022Nov 7, 2022Jul 7, 2023Mar 5, 2024Nov 2, 2024Jul 2, 2025Mar 1, 2026
Updated 8mo ago

Evaluation results

MethodLinks
TAC2026.0350.3
VaMP2025.1149.69
PromptSRC2025.1149.55
PromptSRC2026.0349.55
DeAR2026.0349.5
RPOLearnable=true, shots=16 per class2023.0849.27
FARL2025.1249.23
MMRL2025.1149.17
MMRL2026.0349.17
MaPLe2025.1149.15
MaPLe2025.1249.15
MaPLe2026.0349.15
MMA2025.1149.13
MMA2025.1249.13
CoCoOpLearnable=true, Number of training images per class=162022.0348.75
CoCoOpLearnable=true, shots=16 per class2023.0848.75
CoOpOp2025.1148.75
CoOp2025.1248.75
MMRL2025.1248.7
CoOpLearnable=true, Number of training images per class=162022.0347.99
CoOpLearnable=true, shots=16 per class2023.0847.99
CoOp2025.1147.99
CoOp2026.0347.99
CLIPLearnable=false2022.0346.15
CLIPLearnable=false2023.0846.15
CLIP2025.1146.15
CLIP2025.1246.15
T-DHATraining Type=Training-free2025.1237.92
APETraining Type=Training-free2025.1236.61
Tip-AdapterTraining Type=Training-free2025.1235.9
CALIPTraining Type=Zero-shot2025.1235.61
CLIPTraining Type=Zero-shot2025.1235.44
NOAHShots per category=162022.0624.8
LoRAShots per category=162022.0620
VPTShots per category=162022.0618.3
AdapterShots per category=162022.0616.4