9 citations · 11 across the 4 of their papers we have counts for
4 papers
Hyperbolic Space with Hierarchical Margin Boosts Fine-Grained Learning from Coarse Labels
Shu-Lin Xu, Yifan Sun, Faen Zhang +3
Learning fine-grained embeddings from coarse labels is a challenging task due to limited label granularity supervision, i.e., lacking the detailed distinctions required for fine-gr…
Watch out Venomous Snake Species: A Solution to SnakeCLEF2023
Feiran Hu, Peng Wang, Yangyang Li +6
The SnakeCLEF2023 competition aims to the development of advanced algorithms for snake species identification through the analysis of images and accompanying metadata. This paper p…
Delving Deep into Simplicity Bias for Long-Tailed Image Recognition
Xiu-Shen Wei, Xuhao Sun, Yang Shen +3
Simplicity Bias (SB) is a phenomenon that deep neural networks tend to rely favorably on simpler predictive patterns but ignore some complex features when applied to supervised dis…
An Embarrassingly Simple Approach to Semi-Supervised Few-Shot Learning
Xiu-Shen Wei, He-Yang Xu, Faen Zhang +2
Semi-supervised few-shot learning consists in training a classifier to adapt to new tasks with limited labeled data and a fixed quantity of unlabeled data. Many sophisticated metho…