4 citations · 4 across the 16 of their papers we have counts for
7 papers · 1 filter
Shared Spatial Memory Through Predictive Coding
Zhengru Fang, Yu Guo, Yuang Zhang +3
Constructing a consistent shared spatial memory is a critical challenge in multi-agent systems, where partial observability and limited bandwidth often lead to catastrophic failure…
SAFE-D: A Spatiotemporal Detection Framework for Abnormal Driving Among Parkinson's Disease-like Drivers
Hangcheng Cao, Baixiang Huang, Longzhi Yuan +4
A driver's health state serves as a determinant factor in driving behavioral regulation. Subtle deviations from normalcy can lead to operational anomalies, posing risks to public t…
Neptune-X: Active X-to-Maritime Generation for Universal Maritime Object Detection
Yu Guo, Shengfeng He, Yuxu Lu +5
Maritime object detection is essential for navigation safety, surveillance, and autonomous operations, yet constrained by two key challenges: the scarcity of annotated maritime dat…
Removing Box-Free Watermarks for Image-to-Image Models via Query-Based Reverse Engineering
Haonan An, Guang Hua, Hangcheng Cao +4
The intellectual property of deep generative networks (GNets) can be protected using a cascaded hiding network (HNet) which embeds watermarks (or marks) into GNet outputs, known as…
NWaaS: A Non-Intrusive and Privacy-Preserving Watermarking-as-a-Service System with Adaptive Resource Scheduling
Haonan An, Qianyao Ren, Guang Hua +5
Securing intellectual property (IP) in Machine Learning as a Service is critical yet challenging. While deep neural network watermarking serves as a standard defense against model…
Decoder Gradient Shield: Provable and High-Fidelity Prevention of Gradient-Based Box-Free Watermark Removal
Haonan An, Guang Hua, Zhengru Fang +3
The intellectual property of deep image-to-image models can be protected by the so-called box-free watermarking. It uses an encoder and a decoder, respectively, to embed into and e…
GCP: Guarded Collaborative Perception with Spatial-Temporal Aware Malicious Agent Detection
Yihang Tao, Senkang Hu, Yue Hu +3
Collaborative perception significantly enhances autonomous driving safety by extending each vehicle's perception range through message sharing among connected and autonomous vehicl…