Tasks SotA Datasets Papers Methods Submit About

Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable Benchmarks All SotA Datasets Papers Methods

Community

Submit Results About

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/CAML [Laion-2b]

CAML [Laion-2b]

Reported on 16 benchmarks across 2 tasks · 1 paper · 8 SOTA

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

Computer Vision16 results

Image ClassificationonCUB 200 5-way 5-shot
Accuracy· uses extra data· 2023-10-17
98.7
SOTA
Context-Aware Meta-Learning arXiv:2310.10971
Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· uses extra data· 2023-10-17
96.8
SOTA
Context-Aware Meta-Learning arXiv:2310.10971
Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· uses extra data· 2023-10-17
98.8
SOTA
Context-Aware Meta-Learning arXiv:2310.10971
Image ClassificationonCIFAR-FS 5-way (5-shot)
Accuracy· uses extra data· 2023-10-17
93.5
SOTA
Context-Aware Meta-Learning arXiv:2310.10971
Few-Shot Image ClassificationonCUB 200 5-way 5-shot
Accuracy· uses extra data· 2023-10-17
98.7
SOTA
Context-Aware Meta-Learning arXiv:2310.10971
Few-Shot Image ClassificationonTiered ImageNet 5-way (1-shot)
Accuracy· uses extra data· 2023-10-17
96.8
SOTA
Context-Aware Meta-Learning arXiv:2310.10971
Few-Shot Image ClassificationonTiered ImageNet 5-way (5-shot)
Accuracy· uses extra data· 2023-10-17
98.8
SOTA
Context-Aware Meta-Learning arXiv:2310.10971
Few-Shot Image ClassificationonCIFAR-FS 5-way (5-shot)
Accuracy· uses extra data· 2023-10-17
93.5
SOTA
Context-Aware Meta-Learning arXiv:2310.10971
Image ClassificationonCUB 200 5-way 1-shot
Accuracy· uses extra data· 2023-10-17
95.8
Context-Aware Meta-Learning arXiv:2310.10971
Image ClassificationonCIFAR-FS 5-way (1-shot)
Accuracy· uses extra data· 2023-10-17
83.3
best: 89.94 (PT+MAP+SF+SOT (transductive))
Context-Aware Meta-Learning arXiv:2310.10971
Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· uses extra data· 2023-10-17
98.6
best: 98.72 (SgVA-CLIP)
Context-Aware Meta-Learning arXiv:2310.10971
Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· uses extra data· 2023-10-17
96.2
best: 97.95 (SgVA-CLIP)
Context-Aware Meta-Learning arXiv:2310.10971
Few-Shot Image ClassificationonCUB 200 5-way 1-shot
Accuracy· uses extra data· 2023-10-17
95.8
Context-Aware Meta-Learning arXiv:2310.10971
Few-Shot Image ClassificationonCIFAR-FS 5-way (1-shot)
Accuracy· uses extra data· 2023-10-17
83.3
best: 89.94 (PT+MAP+SF+SOT (transductive))
Context-Aware Meta-Learning arXiv:2310.10971
Few-Shot Image ClassificationonMini-Imagenet 5-way (5-shot)
Accuracy· uses extra data· 2023-10-17
98.6
best: 98.72 (SgVA-CLIP)
Context-Aware Meta-Learning arXiv:2310.10971
Few-Shot Image ClassificationonMini-Imagenet 5-way (1-shot)
Accuracy· uses extra data· 2023-10-17
96.2
best: 97.95 (SgVA-CLIP)
Context-Aware Meta-Learning arXiv:2310.10971