5 citations · 13 across the 4 of their papers we have counts for
4 papers
End-to-End 3-D Spatiotemporal Perception with Multimodal Fusion and V2X Collaboration
Zhenwei Yang, Yibo Ai, Weidong Zhang
Multiview cooperative perception and multimodal fusion are essential for reliable 3-D spatiotemporal understanding in autonomous driving, especially in cases with occlusions, limit…
LiDAR-based End-to-end Temporal Perception for Vehicle-Infrastructure Cooperation
Zhenwei Yang, Jilei Mao, Wenxian Yang +4
Temporal perception, defined as the capability to detect and track objects across temporal sequences, serves as a fundamental component in autonomous driving systems. While single-…
End-to-End Autonomous Driving through V2X Cooperation
Haibao Yu, Wenxian Yang, Jiaru Zhong +4
Cooperatively utilizing both ego-vehicle and infrastructure sensor data via V2X communication has emerged as a promising approach for advanced autonomous driving. However, current…
V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecasting
Haibao Yu, Wenxian Yang, Hongzhi Ruan +11
Utilizing infrastructure and vehicle-side information to track and forecast the behaviors of surrounding traffic participants can significantly improve decision-making and safety i…