42 citations · 85 across the 16 of their papers we have counts for
17 papers · 1 filter
Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks with Implicit Gradients
Kaidong Li, Ziming Zhang, Cuncong Zhong +1
Deep neural networks for 3D point cloud classification, such as PointNet, have been demonstrated to be vulnerable to adversarial attacks. Current adversarial defenders often learn…
ZoomCount: A Zooming Mechanism for Crowd Counting in Static Images
Usman Sajid, Hasan Sajid, Hongcheng Wang +1
This paper proposes a novel approach for crowd counting in low to high density scenarios in static images. Current approaches cannot handle huge crowd diversity well and thus perfo…
Self-Orthogonality Module: A Network Architecture Plug-in for Learning Orthogonal Filters
Ziming Zhang, Wenchi Ma, Yuanwei Wu +1
In this paper, we investigate the empirical impact of orthogonality regularization (OR) in deep learning, either solo or collaboratively. Recent works on OR showed some promising r…
Boosting Occluded Image Classification via Subspace Decomposition Based Estimation of Deep Features
Feng Cen, Guanghui Wang
Classification of partially occluded images is a highly challenging computer vision problem even for the cutting edge deep learning technologies. To achieve a robust image classifi…
Plug-and-Play Rescaling Based Crowd Counting in Static Images
Usman Sajid, Guanghui Wang
Crowd counting is a challenging problem especially in the presence of huge crowd diversity across images and complex cluttered crowd-like background regions, where most previous ap…
MDFN: Multi-Scale Deep Feature Learning Network for Object Detection
Wenchi Ma, Yuanwei Wu, Feng Cen +1
This paper proposes an innovative object detector by leveraging deep features learned in high-level layers. Compared with features produced in earlier layers, the deep features are…