Guangwu Hu — accepted AI-conference papers

2026

FeatureFool: Zero-Query Fooling of Video Models via Feature Map

Duoxun Tang, Xi Xiao, Guangwu Hu, Kangkang Sun, Xiao Yang, Dongyang Chen +3

CVPR 2026

The vulnerability of deep neural networks (DNNs) has been preliminarily verified. Existing black-box adversarial attacks usually require multi-round interaction with the model and consume numerous queries, which is impractical in the real-world and hard to scale to recently emerged Video-LLMs. Moreo

Cited by 0 Source ↗Scholar ↗

2019

Non-local Self-attention Structure for Function Approximation in Deep Reinforcement Learning

Zhixiang Wang, Xi Xiao, Guangwu Hu, Yao Yao, Dianyan Zhang, Zhendong Peng +2

ICASSP 2019accepted

Reinforcement learning is a framework to make sequential decisions. The combination with deep neural networks further improves the ability of this framework. Convolutional nerual networks make it possible to make sequential decisions based on raw pixels information directly and make reinforcement le…

Cited by 0 Source ↗Scholar ↗