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20242026
most citedCP-Guard: Malicious Agent Detection and Defense in Collaborative Bird's Eye View Perception

1 citations · 1 across the 19 of their papers we have counts for

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cs.CV2026

Mobility Helps Learning: Unsupervised Model Adaptation for Object Recognition via Movement

Yanan Ma, Yihang Tao, Zhengru Fang +3

Movable agents, such as autonomous vehicles and robots, should be able to autonomously adapt their pre-trained object recognition models to new environments without human annotatio…

cs.CV2026

Universal Image Restoration via Internalized Chain-of-Thought Reasoning

Yu Guo, Zhengru Fang, Shengfeng He +4

Image restoration seeks to recover high-quality images from degraded inputs but becomes highly ill-posed under complex, mixed degradations. While unified all-in-one models are comm…

cs.CV2026

FRUC: Feedforward Dynamic Scene Reconstruction from Uncalibrated Collaborative Driving Views

Yihang Tao, Yu Guo, Zhengru Fang +2

We present FRUC, a feedforward 3D Gaussian Splatting framework for dynamic scene reconstruction from uncalibrated collaborative driving views. Existing multi-agent reconstruction f…

cs.CV2026

V2VCrafter: Consistent Street-View Image Generation Across Vehicles

Yihang Tao, Yu Guo, Senkang Hu +4

Connected and autonomous driving (CAD) systems leverage vehicle-to-vehicle (V2V) communication for multi-agent collaborative perception, yet remain constrained by scarce annotated…

cs.CV2026

RecoverMark: Robust Watermarking for Localization and Recovery of Manipulated Faces

Haonan An, Xiaohui Ye, Guang Hua +4

The proliferation of AI-generated content has facilitated sophisticated face manipulation, severely undermining visual integrity and posing unprecedented challenges to intellectual…

cs.CV2026

Learning Mutual View Information Graph for Adaptive Adversarial Collaborative Perception

Yihang Tao, Senkang Hu, Haonan An +3

Collaborative perception (CP) enables data sharing among connected and autonomous vehicles (CAVs) to enhance driving safety. However, CP systems are vulnerable to adversarial attac…

cs.CV2026

Decoder Gradient Shields: A Family of Provable and High-Fidelity Methods Against Gradient-Based Box-Free Watermark Removal

Haonan An, Guang Hua, Wei Du +5

Box-free model watermarking has gained significant attention in deep neural network (DNN) intellectual property protection due to its model-agnostic nature and its ability to flexi…

cs.CV2025

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…

cs.CV2025

CP-uniGuard: A Unified, Probability-Agnostic, and Adaptive Framework for Malicious Agent Detection and Defense in Multi-Agent Embodied Perception Systems

Senkang Hu, Yihang Tao, Guowen Xu +5

Collaborative Perception (CP) has been shown to be a promising technique for multi-agent autonomous driving and multi-agent robotic systems, where multiple agents share their perce…

cs.CV2025

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…

cs.CV2024

Directed-CP: Directed Collaborative Perception for Connected and Autonomous Vehicles via Proactive Attention

Yihang Tao, Senkang Hu, Zhengru Fang +1

Collaborative perception (CP) leverages visual data from connected and autonomous vehicles (CAV) to enhance an ego vehicle's field of view (FoV). Despite recent progress, current C…