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Models/LIFT (ViT-B/16, CLIP)

LIFT (ViT-B/16, CLIP)

Reported on 15 benchmarks across 5 tasks · 1 paper

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

Methodology9 results

Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2023-09-18
16.9
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-09-18
15.1
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Generalized Few-Shot ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· uses extra data· 2023-09-18
18.3
best: 10.9 (LPT)
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Long-tail LearningonCIFAR-100-LT (ρ=50)
Error Rate· 2023-09-18
16.9
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Long-tail LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2023-09-18
15.1
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Long-tail LearningonCIFAR-100-LT (ρ=100)
Error Rate· uses extra data· 2023-09-18
18.3
best: 10.9 (LPT)
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=50)
Error Rate· 2023-09-18
16.9
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=10)
Error Rate· 2023-09-18
15.1
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Generalized Few-Shot LearningonCIFAR-100-LT (ρ=100)
Error Rate· uses extra data· 2023-09-18
18.3
best: 10.9 (LPT)
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019

Computer Vision6 results

Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2023-09-18
16.9
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-09-18
15.1
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· uses extra data· 2023-09-18
18.3
best: 10.9 (LPT)
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=50)
Error Rate· 2023-09-18
16.9
best: 9.8 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=10)
Error Rate· 2023-09-18
15.1
best: 8.7 (LIFT (ViT-B/16, ImageNet-21K pre-training))
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019
Few-Shot Image ClassificationonCIFAR-100-LT (ρ=100)
Error Rate· uses extra data· 2023-09-18
18.3
best: 10.9 (LPT)
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts arXiv:2309.10019