SOTAVerified

Cross-Domain Few-Shot

Papers

Showing 51–100 of 141 papers

TitleStatusHype
Leveraging Normalization Layer in Adapters With Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot LearningCode0
Improving Cross-domain Few-shot Classification with Multilayer PerceptronCode1
DARNet: Bridging Domain Gaps in Cross-Domain Few-Shot Segmentation with Dynamic Adaptation—0
Adaptive Weighted Co-Learning for Cross-Domain Few-Shot Learning—0
Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot ClassificationCode1
Multi-level Relation Learning for Cross-domain Few-shot Hyperspectral Image ClassificationCode0
CDFSL-V: Cross-Domain Few-Shot Learning for VideosCode1
RestNet: Boosting Cross-Domain Few-Shot Segmentation with Residual Transformation NetworkCode1
Adaptive Semantic Consistency for Cross-domain Few-shot ClassificationCode0
Task-Oriented Channel Attention for Fine-Grained Few-Shot ClassificationCode1
Mutually Guided Few-shot Learning for Relational Triple ExtractionCode0
Dual Adaptive Representation Alignment for Cross-domain Few-shot LearningCode1
PromptNER: Prompt Locating and Typing for Named Entity RecognitionCode1
Few-shot Class-incremental Learning for Cross-domain Disease Classification—0
A Survey of Deep Visual Cross-Domain Few-Shot Learning—0
Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey—0
Unsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive LearningCode1
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot LearningCode1
Exploiting Style Transfer-based Task Augmentation for Cross-Domain Few-Shot Learning—0
Task-aware Adaptive Learning for Cross-domain Few-shot Learning—0
Revisiting Prototypical Network for Cross Domain Few-Shot LearningCode1
ProD: Prompting-To-Disentangle Domain Knowledge for Cross-Domain Few-Shot Image Classification—0
Cap2Aug: Caption guided Image to Image data Augmentation—0
Cross-Domain Few-Shot Relation Extraction via Representation Learning and Domain Adaptation—0
Rationale-Guided Few-Shot Classification to Detect Abusive LanguageCode0
Cross-domain Few-shot Segmentation with Transductive Fine-tuning—0
TGDM: Target Guided Dynamic Mixup for Cross-Domain Few-Shot LearningCode0
CD-FSOD: A Benchmark for Cross-domain Few-shot Object DetectionCode1
ME-D2N: Multi-Expert Domain Decompositional Network for Cross-Domain Few-Shot LearningCode1
AcroFOD: An Adaptive Method for Cross-domain Few-shot Object DetectionCode1
Adversarial Feature Augmentation for Cross-domain Few-shot ClassificationCode1
Cross-Domain Few-Shot Classification via Inter-Source Stylization—0
Learn-to-Decompose: Cascaded Decomposition Network for Cross-Domain Few-Shot Facial Expression RecognitionCode1
Graph Information Aggregation Cross-Domain Few-Shot Learning for Hyperspectral Image ClassificationCode1
Feature Extractor Stacking for Cross-domain Few-shot LearningCode0
ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning—0
Knowledge Distillation Meets Few-Shot Learning: An Approach for Few-Shot Intent Classification Within and Across Domains—0
Universal Representations: A Unified Look at Multiple Task and Domain LearningCode1
A Framework of Meta Functional Learning for Regularising Knowledge Transfer—0
Cross-Domain Few-Shot Semantic SegmentationCode1
Wave-SAN: Wavelet based Style Augmentation Network for Cross-Domain Few-Shot LearningCode0
Feature Transformation for Cross-domain Few-shot Remote Sensing Scene Classification—0
How Well Do Self-Supervised Methods Perform in Cross-Domain Few-Shot Learning?—0
Cross Domain Few-Shot Learning via Meta Adversarial Training—0
Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot DifficultyCode1
Cross-Domain Few-Shot Graph ClassificationCode0
When Facial Expression Recognition Meets Few-Shot Learning: A Joint and Alternate Learning Framework—0
FrLove : Could a Frenchman rapidly identify Lovecraft?—0
Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning—0
Revisiting Learnable Affines for Batch Norm in Few-Shot Transfer Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1StyleAdv-FT5 shot26.24—Unverified
2StyleAdv5 shot26.07—Unverified
3RFS+MLP5 shot26—Unverified
4BSCD-FSL5 shot25.97—Unverified
5wave-SAN5 shot25.63—Unverified
6GNN5 shot25.27—Unverified
7FWT5 shot25.18—Unverified
8ATA-FT5 shot25.08—Unverified
9AFA5 shot25.02—Unverified
10LRP5 shot24.53—Unverified
#ModelMetricClaimedVerifiedStatus
1StyleAdv-FT5 shot91.64—Unverified
2ATA-FT5 shot89.64—Unverified
3StyleAdv5 shot86.58—Unverified
4AFA5 shot85.58—Unverified
5wave-SAN5 shot85.22—Unverified
6ATA5 shot83.75—Unverified
7GNN5 shot83.64—Unverified
8FWT5 shot83.01—Unverified
9BSCD-FSL5 shot79.08—Unverified
10RFS+MLP5 shot78.13—Unverified
#ModelMetricClaimedVerifiedStatus
1StyleAdv-FT5 shot53.05—Unverified
2ATA-FT5 shot49.79—Unverified
3BSCD-FSL5 shot48.11—Unverified
4RFS+MLP5 shot46.33—Unverified
5AFA5 shot46.01—Unverified
6StyleAdv5 shot45.77—Unverified
7wave-SAN5 shot44.93—Unverified
8ATA5 shot44.91—Unverified
9LRP5 shot44.14—Unverified
10GNN5 shot43.94—Unverified
#ModelMetricClaimedVerifiedStatus
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
8AFA5 shot88.06—Unverified
9FWT5 shot87.11—Unverified
#ModelMetricClaimedVerifiedStatus
1MSENet5 shot71.59—Unverified
2StyleAdv-FT5 shot70.9—Unverified
3wave-SAN5 shot70.31—Unverified
4ATA-FT5 shot69.83—Unverified
5StyleAdv5 shot68.72—Unverified
6AFA5 shot68.25—Unverified
7FWT5 shot66.98—Unverified
8ATA5 shot66.22—Unverified
9BSCD-FSL5 shot64.14—Unverified
#ModelMetricClaimedVerifiedStatus
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
#ModelMetricClaimedVerifiedStatus
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
#ModelMetricClaimedVerifiedStatus
1StyleAdv-FT5 shot64.1—Unverified
2StyleAdv5 shot61.52—Unverified
3BSCD-FSL5 shot59.27—Unverified
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