19 citations · 41 across the 4 of their papers we have counts for
6 papers
What You See is Not What the Network Infers: Detecting Adversarial Examples Based on Semantic Contradiction
Yijun Yang, Ruiyuan Gao, Yu Li +2
Adversarial examples (AEs) pose severe threats to the applications of deep neural networks (DNNs) to safety-critical domains, e.g., autonomous driving. While there has been a vast…
TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks
Yu Li, Min Li, Qiuxia Lai +2
Deep learning (DL) has achieved unprecedented success in a variety of tasks. However, DL systems are notoriously difficult to test and debug due to the lack of explainability of DL…
T-WaveNet: Tree-Structured Wavelet Neural Network for Sensor-Based Time Series Analysis
Minhao Liu, Ailing Zeng, Qiuxia Lai +1
Sensor-based time series analysis is an essential task for applications such as activity recognition and brain-computer interface. Recently, features extracted with deep neural net…
DeepFuse: An IMU-Aware Network for Real-Time 3D Human Pose Estimation from Multi-View Image
Fuyang Huang, Ailing Zeng, Minhao Liu +2
In this paper, we propose a two-stage fully 3D network, namely \textbf{DeepFuse}, to estimate human pose in 3D space by fusing body-worn Inertial Measurement Unit (IMU) data and mu…
Understanding More about Human and Machine Attention in Deep Neural Networks
Qiuxia Lai, Salman Khan, Yongwei Nie +3
Human visual system can selectively attend to parts of a scene for quick perception, a biological mechanism known as Human attention. Inspired by this, recent deep learning models…
Salient Object Detection in the Deep Learning Era: An In-Depth Survey
Wenguan Wang, Qiuxia Lai, Huazhu Fu +3
As an essential problem in computer vision, salient object detection (SOD) has attracted an increasing amount of research attention over the years. Recent advances in SOD are predo…