10 citations · 27 across the 6 of their papers we have counts for
7 papers
Global Weighted Tensor Nuclear Norm for Tensor Robust Principal Component Analysis
Libin Wang, Yulong Wang, Shiyuan Wang +4
Tensor Robust Principal Component Analysis (TRPCA), which aims to recover a low-rank tensor corrupted by sparse noise, has attracted much attention in many real applications. This…
Analyzing Adversarial Robustness of Deep Neural Networks in Pixel Space: a Semantic Perspective
Lina Wang, Xingshu Chen, Yulong Wang +4
The vulnerability of deep neural networks to adversarial examples, which are crafted maliciously by modifying the inputs with imperceptible perturbations to misled the network prod…
Semantic Segmentation by Improved Generative Adversarial Networks
ZengShun Zhaoa, Yulong Wang, Ke Liu +3
While most existing segmentation methods usually combined the powerful feature extraction capabilities of CNNs with Conditional Random Fields (CRFs) post-processing, the result alw…
6D Object Pose Regression via Supervised Learning on Point Clouds
Ge Gao, Mikko Lauri, Yulong Wang +3
This paper addresses the task of estimating the 6 degrees of freedom pose of a known 3D object from depth information represented by a point cloud. Deep features learned by convolu…
Interpretable Disentanglement of Neural Networks by Extracting Class-Specific Subnetwork
Yulong Wang, Xiaolin Hu, Hang Su
We propose a novel perspective to understand deep neural networks in an interpretable disentanglement form. For each semantic class, we extract a class-specific functional subnetwo…
Pruning from Scratch
Yulong Wang, Xiaolu Zhang, Lingxi Xie +4
Network pruning is an important research field aiming at reducing computational costs of neural networks. Conventional approaches follow a fixed paradigm which first trains a large…