activity
20212023
most citedAlleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid

8 citations · 14 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023

Generalized Category Discovery with Clustering Assignment Consistency

Xiangli Yang, Xinglin Pan, Irwin King +1

Generalized category discovery (GCD) is a recently proposed open-world task. Given a set of images consisting of labeled and unlabeled instances, the goal of GCD is to automaticall…

cs.CV2022★ 8 cited

Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid

Jing Xu, Xu Luo, Xinglin Pan +3

Few-shot learning (FSL) targets at generalization of vision models towards unseen tasks without sufficient annotations. Despite the emergence of a number of few-shot learning metho…

cs.CV2021★ 4 cited

Exploring Category-correlated Feature for Few-shot Image Classification

Jing Xu, Xinglin Pan, Xu Luo +2

Few-shot classification aims to adapt classifiers to novel classes with a few training samples. However, the insufficiency of training data may cause a biased estimation of feature…

cs.CV2021

AFINet: Attentive Feature Integration Networks for Image Classification

Xinglin Pan, Jing Xu, Yu Pan +4

Convolutional Neural Networks (CNNs) have achieved tremendous success in a number of learning tasks including image classification. Recent advanced models in CNNs, such as ResNets,…

eess.IV2021★ 2 cited

RegNet: Self-Regulated Network for Image Classification

Jing Xu, Yu Pan, Xinglin Pan +3

The ResNet and its variants have achieved remarkable successes in various computer vision tasks. Despite its success in making gradient flow through building blocks, the simple sho…