8 citations · 17 across the 6 of their papers we have counts for
4 papers · 1 filter
Multi-Level Correlation Network For Few-Shot Image Classification
Yunkai Dang, Min Zhang, Zhengyu Chen +4
Few-shot image classification(FSIC) aims to recognize novel classes given few labeled images from base classes. Recent works have achieved promising classification performance, esp…
Understanding Prompt Tuning for V-L Models Through the Lens of Neural Collapse
Didi Zhu, Zexi Li, Min Zhang +6
Large-scale vision-language (V-L) models have demonstrated remarkable generalization capabilities for downstream tasks through prompt tuning. However, the mechanisms behind the lea…
RotoGBML: Towards Out-of-Distribution Generalization for Gradient-Based Meta-Learning
Min Zhang, Zifeng Zhuang, Zhitao Wang +2
Gradient-based meta-learning (GBML) algorithms are able to fast adapt to new tasks by transferring the learned meta-knowledge, while assuming that all tasks come from the same dist…
Attributes-Guided and Pure-Visual Attention Alignment for Few-Shot Recognition
Siteng Huang, Min Zhang, Yachen Kang +1
The purpose of few-shot recognition is to recognize novel categories with a limited number of labeled examples in each class. To encourage learning from a supplementary view, recen…