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Models/LPT

LPT

Reported on 20 benchmarks across 5 tasks · 1 paper · 20 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology12 results

Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· uses extra data· 2022-10-03
10
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· uses extra data· 2022-10-03
9
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· uses extra data· 2022-10-03
10.9
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Generalized Few-Shot ClassificationonCIFAR-10-LT (ρ=100)
Error Rate· uses extra data· 2022-10-03
10.9
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Long-tail LearningonCIFAR-100-LT (ρ=50)
Error Rate· uses extra data· 2022-10-03
10
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Long-tail LearningonCIFAR-100-LT (ρ=10)
Error Rate· uses extra data· 2022-10-03
9
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Long-tail LearningonCIFAR-100-LT (ρ=100)
Error Rate· uses extra data· 2022-10-03
10.9
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Long-tail LearningonCIFAR-10-LT (ρ=100)
Error Rate· uses extra data· 2022-10-03
10.9
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=50)
Error Rate· uses extra data· 2022-10-03
10
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=10)
Error Rate· uses extra data· 2022-10-03
9
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=100)
Error Rate· uses extra data· 2022-10-03
10.9
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Generalized Few-Shot LearningonCIFAR-10-LT (ρ=100)
Error Rate· uses extra data· 2022-10-03
10.9
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033

Computer Vision8 results

Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· uses extra data· 2022-10-03
10
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· uses extra data· 2022-10-03
9
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· uses extra data· 2022-10-03
10.9
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Image ClassificationonCIFAR-10-LT (ρ=100)
Error Rate· uses extra data· 2022-10-03
10.9
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· uses extra data· 2022-10-03
10
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· uses extra data· 2022-10-03
9
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· uses extra data· 2022-10-03
10.9
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033
Few-Shot Image ClassificationonCIFAR-10-LT (ρ=100)
Error Rate· uses extra data· 2022-10-03
10.9
best: 10.42 (GLMC+MaxNorm (ResNet-34, channel x4))
SOTA
LPT: Long-tailed Prompt Tuning for Image Classification arXiv:2210.01033