211 citations · 1k across the 37 of their papers we have counts for
14 papers · 1 filter
Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations
Pu Zhao, Parikshit Ram, Songtao Lu +4
Adversarial perturbations are critical for certifying the robustness of deep learning models. A universal adversarial perturbation (UAP) can simultaneously attack multiple images,…
Towards Real-Time DNN Inference on Mobile Platforms with Model Pruning and Compiler Optimization
Wei Niu, Pu Zhao, Zheng Zhan +3
High-end mobile platforms rapidly serve as primary computing devices for a wide range of Deep Neural Network (DNN) applications. However, the constrained computation and storage re…
Multi-Person Pose Estimation with Enhanced Feature Aggregation and Selection
Xixia Xu, Qi Zou, Xue Lin
We propose a novel Enhanced Feature Aggregation and Selection network (EFASNet) for multi-person 2D human pose estimation. Due to enhanced feature representation, our method can we…
Security of Deep Learning based Lane Keeping System under Physical-World Adversarial Attack
Takami Sato, Junjie Shen, Ningfei Wang +3
Lane-Keeping Assistance System (LKAS) is convenient and widely available today, but also extremely security and safety critical. In this work, we design and implement the first sys…
A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework
Yifan Gong, Zheng Zhan, Zhengang Li +8
Weight pruning of deep neural networks (DNNs) has been proposed to satisfy the limited storage and computing capability of mobile edge devices. However, previous pruning methods ma…
Towards an Efficient and General Framework of Robust Training for Graph Neural Networks
Kaidi Xu, Sijia Liu, Pin-Yu Chen +4
Graph Neural Networks (GNNs) have made significant advances on several fundamental inference tasks. As a result, there is a surge of interest in using these models for making poten…