111 citations · 347 across the 39 of their papers we have counts for
4 papers · 1 filter
SEMICON: A Learning-to-hash Solution for Large-scale Fine-grained Image Retrieval
Yang Shen, Xuhao Sun, Xiu-Shen Wei +2
In this paper, we propose Suppression-Enhancing Mask based attention and Interactive Channel transformatiON (SEMICON) to learn binary hash codes for dealing with large-scale fine-g…
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…
Bridge the Gap between Supervised and Unsupervised Learning for Fine-Grained Classification
Jiabao Wang, Yang Li, Xiu-Shen Wei +3
Unsupervised learning technology has caught up with or even surpassed supervised learning technology in general object classification (GOC) and person re-identification (re-ID). Ho…
Relieving Long-tailed Instance Segmentation via Pairwise Class Balance
Yin-Yin He, Peizhen Zhang, Xiu-Shen Wei +2
Long-tailed instance segmentation is a challenging task due to the extreme imbalance of training samples among classes. It causes severe biases of the head classes (with majority s…