SOTAVerified

Cross-Domain Few-Shot

Papers

Showing 101–141 of 141 papers

TitleStatusHype
Remember the Difference: Cross-Domain Few-Shot Semantic Segmentation via Meta-Memory Transfer—0
Anomaly Crossing: New Horizons for Video Anomaly Detection as Cross-domain Few-shot Learning—0
Ranking Distance Calibration for Cross-Domain Few-Shot Learning—0
CQARE: Contrastive Question-Answering for Few-shot Relation Extraction with Prompt Tuning—0
Domain Agnostic Few-Shot Learning For Document Intelligence—0
Pixel-by-Pixel Cross-Domain Alignment for Few-Shot Semantic SegmentationCode1
Contextual Gradient Scaling for Few-Shot LearningCode0
On Label-Efficient Computer Vision: Building Fast and Effective Few-Shot Image Classifiers—0
Switch to Generalize: Domain-Switch Learning for Cross-Domain Few-Shot Classification—0
ConFeSS: A Framework for Single Source Cross-Domain Few-Shot Learning—0
MemREIN: Rein the Domain Shift for Cross-Domain Few-Shot Learning—0
Self-Taught Cross-Domain Few-Shot Learning with Weakly Supervised Object Localization and Task-Decomposition—0
Boosting the Generalization Capability in Cross-Domain Few-shot Learning via Noise-enhanced Supervised AutoencoderCode0
Semi-supervised Meta-learning for Cross-domain Few-shot Intent Classification—0
Meta-FDMixup: Cross-Domain Few-Shot Learning Guided by Labeled Target DataCode1
Improving the Generalization of Meta-learning on Unseen Domains via Adversarial Shift—0
Cross-domain Few-shot Learning with Task-specific AdaptersCode1
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter OptimizationCode1
Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled DataCode1
DAMSL: Domain Agnostic Meta Score-based LearningCode0
Cross-Domain Few-Shot Classification via Adversarial Task AugmentationCode1
Modular Adaptation for Cross-Domain Few-Shot LearningCode0
Cross-domain few-shot learning with unlabelled data—0
Machine learning with limited data—0
Shallow Bayesian Meta Learning for Real-World Few-Shot RecognitionCode1
Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple ClassifierCode1
SB-MTL: Score-based Meta Transfer-Learning for Cross-Domain Few-Shot Learning—0
Few-Shot Classification with Feature Map Reconstruction NetworksCode1
Combining Domain-Specific Meta-Learners in the Parameter Space for Cross-Domain Few-Shot Classification—0
Cross-Domain Few-Shot Learning by Representation FusionCode1
Revisiting Mid-Level Patterns for Cross-Domain Few-Shot Recognition—0
Explanation-Guided Training for Cross-Domain Few-Shot ClassificationCode1
A Transductive Multi-Head Model for Cross-Domain Few-Shot LearningCode0
Ensemble Model with Batch Spectral Regularization and Data Blending for Cross-Domain Few-Shot Learning with Unlabeled DataCode0
Cross-Domain Few-Shot Learning with Meta Fine-Tuning—0
Large Margin Mechanism and Pseudo Query Set on Cross-Domain Few-Shot Learning—0
Feature Transformation Ensemble Model with Batch Spectral Regularization for Cross-Domain Few-Shot Classification—0
Cross-Domain Few-Shot Classification via Learned Feature-Wise TransformationCode1
A Broader Study of Cross-Domain Few-Shot LearningCode1
Self-Supervised Learning For Few-Shot Image ClassificationCode0
Few-Shot Learning with Graph Neural NetworksCode0
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Benchmark Results

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2StyleAdv5 shot26.07—Unverified
3RFS+MLP5 shot26—Unverified
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6GNN5 shot25.27—Unverified
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10LRP5 shot24.53—Unverified
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2ATA-FT5 shot89.64—Unverified
3StyleAdv5 shot86.58—Unverified
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5wave-SAN5 shot85.22—Unverified
6ATA5 shot83.75—Unverified
7GNN5 shot83.64—Unverified
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9BSCD-FSL5 shot79.08—Unverified
10RFS+MLP5 shot78.13—Unverified
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1StyleAdv-FT5 shot53.05—Unverified
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5AFA5 shot46.01—Unverified
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10GNN5 shot43.94—Unverified
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1StyleAdv-FT5 shot96.51—Unverified
2ATA-FT5 shot95.44—Unverified
3StyleAdv5 shot93.65—Unverified
4ATA5 shot90.59—Unverified
5wave-SAN5 shot89.7—Unverified
6RFS+MLP5 shot89.68—Unverified
7BSCD-FSL5 shot89.25—Unverified
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9FWT5 shot87.11—Unverified
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7FWT5 shot66.98—Unverified
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9BSCD-FSL5 shot64.14—Unverified
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1StyleAdv-FT5 shot56.44—Unverified
2ATA-FT5 shot54.28—Unverified
3BSCD-FSL5 shot52.08—Unverified
4StyleAdv5 shot50.13—Unverified
5AFA5 shot49.28—Unverified
6ATA5 shot49.14—Unverified
7wave-SAN5 shot46.11—Unverified
8FWT5 shot44.9—Unverified
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1StyleAdv-FT5 shot79.35—Unverified
2StyleAdv5 shot77.73—Unverified
3wave-SAN5 shot76.88—Unverified
4ATA-FT5 shot76.64—Unverified
5AFA5 shot76.21—Unverified
6ATA5 shot75.48—Unverified
7FWT5 shot73.94—Unverified
8BSCD-FSL5 shot70.06—Unverified
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1StyleAdv-FT5 shot64.1—Unverified
2StyleAdv5 shot61.52—Unverified
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4ATA-FT5 shot58.08—Unverified
5wave-SAN5 shot57.72—Unverified
6AFA5 shot54.26—Unverified
7FWT5 shot53.85—Unverified
8ATA5 shot52.69—Unverified
#ModelMetricClaimedVerifiedStatus
1Domain Agnostic Meta Score-based LearningAccuracy (%)74.99—Unverified