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cross-domain few-shot learning

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

Papers

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Showing 71–74 of 74 papers

Title	Date	Tasks	Status
Contextual Interaction via Primitive-based Adversarial Training For Compositional Zero-shot Learning	Jun 21, 2024	AttributeCompositional Zero-Shot Learning	CodeCode Available
SVasP: Self-Versatility Adversarial Style Perturbation for Cross-Domain Few-Shot Learning	Dec 12, 2024	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available
Wave-SAN: Wavelet based Style Augmentation Network for Cross-Domain Few-Shot Learning	Mar 15, 2022	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available
A Transductive Multi-Head Model for Cross-Domain Few-Shot Learning	Jun 8, 2020	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available

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