23 citations · 59 across the 9 of their papers we have counts for
13 papers
Parallel Rectangle Flip Attack: A Query-based Black-box Attack against Object Detection
Siyuan Liang, Baoyuan Wu, Yanbo Fan +2
Object detection has been widely used in many safety-critical tasks, such as autonomous driving. However, its vulnerability to adversarial examples has not been sufficiently studie…
An Effective and Robust Detector for Logo Detection
Xiaojun Jia, Huanqian Yan, Yonglin Wu +3
In recent years, intellectual property (IP), which represents literary, inventions, artistic works, etc, gradually attract more and more people's attention. Particularly, with the…
Automated Model Compression by Jointly Applied Pruning and Quantization
Wenting Tang, Xingxing Wei, Bo Li
In the traditional deep compression framework, iteratively performing network pruning and quantization can reduce the model size and computation cost to meet the deployment require…
Object Hider: Adversarial Patch Attack Against Object Detectors
Yusheng Zhao, Huanqian Yan, Xingxing Wei
Deep neural networks have been widely used in many computer vision tasks. However, it is proved that they are susceptible to small, imperceptible perturbations added to the input.…
Adv-watermark: A Novel Watermark Perturbation for Adversarial Examples
Xiaojun Jia, Xingxing Wei, Xiaochun Cao +1
Recent research has demonstrated that adding some imperceptible perturbations to original images can fool deep learning models. However, the current adversarial perturbations are u…
Efficient Adversarial Attacks for Visual Object Tracking
Siyuan Liang, Xingxing Wei, Siyuan Yao +1
Visual object tracking is an important task that requires the tracker to find the objects quickly and accurately. The existing state-ofthe-art object trackers, i.e., Siamese based…