26 citations · 45 across the 8 of their papers we have counts for
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cs.CV2025
Few-shot Classification as Multi-instance Verification: Effective Backbone-agnostic Transfer across Domains
Xin Xu, Eibe Frank, Geoffrey Holmes
We investigate cross-domain few-shot learning under the constraint that fine-tuning of backbones (i.e., feature extractors) is impossible or infeasible---a scenario that is increas…
cs.CV2022★ 1 cited
Feature Extractor Stacking for Cross-domain Few-shot Learning
Hongyu Wang, Eibe Frank, Bernhard Pfahringer +2
Cross-domain few-shot learning (CDFSL) addresses learning problems where knowledge needs to be transferred from one or more source domains into an instance-scarce target domain wit…