activity
20182022
most citedJoint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification

19 citations · 20 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV202219 cited

Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification

Jiangtao Xie, Fei Long, Jiaming Lv +2

Few-shot classification is a challenging problem as only very few training examples are given for each new task. One of the effective research lines to address this challenge focus…

cs.CV20211 cited

Binocular Mutual Learning for Improving Few-shot Classification

Ziqi Zhou, Xi Qiu, Jiangtao Xie +2

Most of the few-shot learning methods learn to transfer knowledge from datasets with abundant labeled data (i.e., the base set). From the perspective of class space on base set, ex…

cs.CV2021

3rd Place Solution for Short-video Face Parsing Challenge

Xiao Liu, Xiaofei Si, Jiangtao Xie

This is a short technical report introducing the solution of Team Rat for Short-video Parsing Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Challenge at CVPR 2…

cs.CV2019

Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization

Qilong Wang, Jiangtao Xie, Wangmeng Zuo +2

Compared with global average pooling in existing deep convolutional neural networks (CNNs), global covariance pooling can capture richer statistics of deep features, having potenti…

cs.CV2018

Global Second-order Pooling Convolutional Networks

Zilin Gao, Jiangtao Xie, Qilong Wang +1

Deep Convolutional Networks (ConvNets) are fundamental to, besides large-scale visual recognition, a lot of vision tasks. As the primary goal of the ConvNets is to characterize com…