41 citations · 70 across the 35 of their papers we have counts for
13 papers · 1 filter
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…
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…
CXR-ContraBench: Benchmarking Negated-Option Attraction in Medical VLMs
Zhengru Fang, Yanan Ma, Yu Guo +5
When a chest X-ray shows consolidation but the question asks which finding is present, a medical vision-language model may answer "No consolidation." This is more than an incorrect…
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…
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…
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…
Task-Oriented Semantic Compression for Localization at the Network Edge
Zhengru Fang, Senkang Hu, Yu Guo +2
Achieving precise visual localization in GPS-limited urban environments poses significant challenges for resource-constrained mobile platforms, particularly under strict bandwidth,…
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…
IC3M: In-Car Multimodal Multi-object Monitoring for Abnormal Status of Both Driver and Passengers
Zihan Fang, Zheng Lin, Senkang Hu +4
Recently, in-car monitoring has emerged as a promising technology for detecting early-stage abnormal status of the driver and providing timely alerts to prevent traffic accidents.…
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…
AgentsCoMerge: Large Language Model Empowered Collaborative Decision Making for Ramp Merging
Senkang Hu, Zhengru Fang, Zihan Fang +4
Ramp merging is one of the bottlenecks in traffic systems, which commonly cause traffic congestion, accidents, and severe carbon emissions. In order to address this essential issue…
Collaborative Perception for Connected and Autonomous Driving: Challenges, Possible Solutions and Opportunities
Senkang Hu, Zhengru Fang, Yiqin Deng +2
Autonomous driving has attracted significant attention from both academia and industries, which is expected to offer a safer and more efficient driving system. However, current aut…
Towards Full-scene Domain Generalization in Multi-agent Collaborative Bird's Eye View Segmentation for Connected and Autonomous Driving
Senkang Hu, Zhengru Fang, Yiqin Deng +3
Collaborative perception has recently gained significant attention in autonomous driving, improving perception quality by enabling the exchange of additional information among vehi…