1 citations · 1 across the 8 of their papers we have counts for
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Physical Adversarial Attack on Monocular Depth Estimation via Shape-Varying Patches
Chenxing Zhao, Yang Li, Shihao Wu +3
Adversarial attacks against monocular depth estimation (MDE) systems pose significant challenges, particularly in safety-critical applications such as autonomous driving. Existing…
Flexible Physical Camouflage Generation Based on a Differential Approach
Yang Li, Wenyi Tan, Tingrui Wang +2
This study introduces a novel approach to neural rendering, specifically tailored for adversarial camouflage, within an extensive 3D rendering framework. Our method, named FPA, goe…
DOEPatch: Dynamically Optimized Ensemble Model for Adversarial Patches Generation
Wenyi Tan, Yang Li, Chenxing Zhao +2
Object detection is a fundamental task in various applications ranging from autonomous driving to intelligent security systems. However, recognition of a person can be hindered whe…
A Sea-Land Clutter Classification Framework for Over-the-Horizon-Radar Based on Weighted Loss Semi-supervised GAN
Xiaoxuan Zhang, Zengfu Wang, Kun Lu +2
Deep convolutional neural network has made great achievements in sea-land clutter classification for over-the-horizon-radar (OTHR). The premise is that a large number of labeled tr…