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/StyleAdv

StyleAdv

Reported on 24 benchmarks across 3 tasks · 1 paper

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

Methodology16 results

Few-Shot LearningonChestX
5 shot· 2023-02-18
26.07
best: 26.24 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Few-Shot LearningonPlantae
5 shot· 2023-02-18
61.52
best: 64.1 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Few-Shot Learningoncars
5 shot· 2023-02-18
50.13
best: 56.44 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Few-Shot LearningonEuroSAT
5 shot· 2023-02-18
86.58
best: 91.64 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Few-Shot LearningonCUB
5 shot· 2023-02-18
68.72
best: 71.59 (MSENet)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Few-Shot LearningonISIC2018
5 shot· 2023-02-18
45.77
best: 53.05 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Few-Shot LearningonPlaces
5 shot· 2023-02-18
77.73
best: 79.35 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Few-Shot LearningonCropDisease
5 shot· 2023-02-18
93.65
best: 96.51 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Meta-LearningonChestX
5 shot· 2023-02-18
26.07
best: 26.24 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Meta-LearningonPlantae
5 shot· 2023-02-18
61.52
best: 64.1 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Meta-Learningoncars
5 shot· 2023-02-18
50.13
best: 56.44 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Meta-LearningonEuroSAT
5 shot· 2023-02-18
86.58
best: 91.64 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Meta-LearningonCUB
5 shot· 2023-02-18
68.72
best: 71.59 (MSENet)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Meta-LearningonISIC2018
5 shot· 2023-02-18
45.77
best: 53.05 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Meta-LearningonPlaces
5 shot· 2023-02-18
77.73
best: 79.35 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Meta-LearningonCropDisease
5 shot· 2023-02-18
93.65
best: 96.51 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309

Computer Vision8 results

Cross-Domain Few-ShotonChestX
5 shot· 2023-02-18
26.07
best: 26.24 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Cross-Domain Few-ShotonPlantae
5 shot· 2023-02-18
61.52
best: 64.1 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Cross-Domain Few-Shotoncars
5 shot· 2023-02-18
50.13
best: 56.44 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Cross-Domain Few-ShotonEuroSAT
5 shot· 2023-02-18
86.58
best: 91.64 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Cross-Domain Few-ShotonCUB
5 shot· 2023-02-18
68.72
best: 71.59 (MSENet)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Cross-Domain Few-ShotonISIC2018
5 shot· 2023-02-18
45.77
best: 53.05 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Cross-Domain Few-ShotonPlaces
5 shot· 2023-02-18
77.73
best: 79.35 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309
Cross-Domain Few-ShotonCropDisease
5 shot· 2023-02-18
93.65
best: 96.51 (StyleAdv-FT)
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning arXiv:2302.09309