activity
20242026
collaborators

7 papers

cs.CV2026

QuantV2X: A Fully Quantized Multi-Agent System for Cooperative Perception

Seth Z. Zhao, Huizhi Zhang, Zhaowei Li +11

Cooperative perception through Vehicle-to-Everything (V2X) communication offers significant potential for enhancing vehicle perception by mitigating occlusions and expanding the fi…

cs.CV2025

MIC-BEV: Multi-Infrastructure Camera Bird's-Eye-View Transformer with Relation-Aware Fusion for 3D Object Detection

Yun Zhang, Zhaoliang Zheng, Johnson Liu +5

Infrastructure-based perception plays a crucial role in intelligent transportation systems, offering global situational awareness and enabling cooperative autonomy. However, existi…

eess.SY2025

CDA-SimBoost: A Unified Framework Bridging Real Data and Simulation for Infrastructure-Based CDA Systems

Zhaoliang Zheng, Xu Han, Yuxin Bao +5

Cooperative Driving Automation (CDA) has garnered increasing research attention, yet the role of intelligent infrastructure remains insufficiently explored. Existing solutions offe…

cs.RO2025

InSPE: Rapid Evaluation of Heterogeneous Multi-Modal Infrastructure Sensor Placement

Zhaoliang Zheng, Yun Zhang, Zongling Meng +3

Infrastructure sensing is vital for traffic monitoring at safety hotspots (e.g., intersections) and serves as the backbone of cooperative perception in autonomous driving. While ve…

cs.CV2024

V2X-Real: a Large-Scale Dataset for Vehicle-to-Everything Cooperative Perception

Hao Xiang, Zhaoliang Zheng, Xin Xia +15

Recent advancements in Vehicle-to-Everything (V2X) technologies have enabled autonomous vehicles to share sensing information to see through occlusions, greatly boosting the percep…

cs.CV2024

AgentAlign: Misalignment-Adapted Multi-Agent Perception for Resilient Inter-Agent Sensor Correlations

Zonglin Meng, Yun Zhang, Zhaoliang Zheng +2

Cooperative perception has attracted wide attention given its capability to leverage shared information across connected automated vehicles (CAVs) and smart infrastructures to addr…