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cross-domain few-shot learning
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Its essence is transfer learning. The model needs to be trained in the source domain and then migrated to the target domain. Compliant with (1) the category in the target domain has never appeared in the source domain (2) the data distribution of the target domain is inconsistent with the source domain (3) each class in the target domain has very few labels
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A Cross-Domain Few-Shot Learning Method Based on Domain Knowledge Mapping
From Dataset to Real-world: General 3D Object Detection via Generalized Cross-domain Few-shot Learning
Reconstruction Target Matters in Masked Image Modeling for Cross-Domain Few-Shot Learning
Task-Specific Preconditioner for Cross-Domain Few-Shot Learning
Enhancing Masked Time-Series Modeling via Dropping Patches
SVasP: Self-Versatility Adversarial Style Perturbation for Cross-Domain Few-Shot Learning
Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting
Step-wise Distribution Alignment Guided Style Prompt Tuning for Source-free Cross-domain Few-shot Learning
Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning
Exploring Cross-Domain Few-Shot Classification via Frequency-Aware Prompting
Contextual Interaction via Primitive-based Adversarial Training For Compositional Zero-shot Learning
Understanding the Cross-Domain Capabilities of Video-Based Few-Shot Action Recognition Models
Multimodal Cross-Domain Few-Shot Learning for Egocentric Action Recognition
A comprehensive and easy-to-use multi-domain multi-task medical imaging meta-dataset (MedIMeta)
Discriminative Sample-Guided and Parameter-Efficient Feature Space Adaptation for Cross-Domain Few-Shot Learning
Enhancing Information Maximization with Distance-Aware Contrastive Learning for Source-Free Cross-Domain Few-Shot Learning
Flatten Long-Range Loss Landscapes for Cross-Domain Few-Shot Learning
Cross-Domain Few-Shot Learning via Adaptive Transformer Networks
Leveraging Normalization Layer in Adapters With Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning
Adaptive Weighted Co-Learning for Cross-Domain Few-Shot Learning
Multi-level Relation Learning for Cross-domain Few-shot Hyperspectral Image Classification
Domain Adaptive Few-Shot Open-Set Learning
CDFSL-V: Cross-Domain Few-Shot Learning for Videos
Dual Adaptive Representation Alignment for Cross-domain Few-shot Learning
A Survey of Deep Visual Cross-Domain Few-Shot Learning
Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning
Exploiting Style Transfer-based Task Augmentation for Cross-Domain Few-Shot Learning
ME-D2N: Multi-Expert Domain Decompositional Network for Cross-Domain Few-Shot Learning
TGDM: Target Guided Dynamic Mixup for Cross-Domain Few-Shot Learning
Self-Supervision Can Be a Good Few-Shot Learner
Learn-to-Decompose: Cascaded Decomposition Network for Cross-Domain Few-Shot Facial Expression Recognition
Graph Information Aggregation Cross-Domain Few-Shot Learning for Hyperspectral Image Classification
Feature Extractor Stacking for Cross-domain Few-shot Learning
ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning
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