154 citations · 509 across the 39 of their papers we have counts for
9 papers · 1 filter
Semantic Regularization: Improve Few-shot Image Classification by Reducing Meta Shift
Da Chen, Yongliang Yang, Zunlei Feng +6
Few-shot image classification requires the classifier to robustly cope with unseen classes even if there are only a few samples for each class. Recent advances benefit from the met…
AdvKnn: Adversarial Attacks On K-Nearest Neighbor Classifiers With Approximate Gradients
Xiaodan Li, Yuefeng Chen, Yuan He +1
Deep neural networks have been shown to be vulnerable to adversarial examples---maliciously crafted examples that can trigger the target model to misbehave by adding imperceptible…
Learning To Characterize Adversarial Subspaces
Xiaofeng Mao, Yuefeng Chen, Yuhong Li +2
Deep Neural Networks (DNNs) are known to be vulnerable to the maliciously generated adversarial examples. To detect these adversarial examples, previous methods use artificially de…
Self-supervised Adversarial Training
Kejiang Chen, Hang Zhou, Yuefeng Chen +6
Recent work has demonstrated that neural networks are vulnerable to adversarial examples. To escape from the predicament, many works try to harden the model in various ways, in whi…
Self-Supervised Learning For Few-Shot Image Classification
Da Chen, Yuefeng Chen, Yuhong Li +3
Few-shot image classification aims to classify unseen classes with limited labelled samples. Recent works benefit from the meta-learning process with episodic tasks and can fast ad…
DeGNN: Characterizing and Improving Graph Neural Networks with Graph Decomposition
Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang +17
Despite the wide application of Graph Convolutional Network (GCN), one major limitation is that it does not benefit from the increasing depth and suffers from the oversmoothing pro…
Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network
Feng Mao, Xiang Wu, Hui Xue +1
High accuracy video label prediction (classification) models are attributed to large scale data. These data could be frame feature sequences extracted by a pre-trained convolutiona…
Bilinear Representation for Language-based Image Editing Using Conditional Generative Adversarial Networks
Xiaofeng Mao, Yuefeng Chen, Yuhong Li +3
The task of Language-Based Image Editing (LBIE) aims at generating a target image by editing the source image based on the given language description. The main challenge of LBIE is…
Deep Features Analysis with Attention Networks
Shipeng Xie, Da Chen, Rong Zhang +1
Deep neural network models have recently draw lots of attention, as it consistently produce impressive results in many computer vision tasks such as image classification, object de…