35 citations · 72 across the 7 of their papers we have counts for
7 papers
Coexistence of multiuser entanglement distribution and classical light in optical fiber network with a semiconductor chip
Xu Jing, Cheng Qian, Hu Nian +10
Building communication links among multiple users in a scalable and robust way is a key objective in achieving large-scale quantum networks. In realistic scenario, noise from the c…
StreamMapNet: Streaming Mapping Network for Vectorized Online HD Map Construction
Tianyuan Yuan, Yicheng Liu, Yue Wang +2
High-Definition (HD) maps are essential for the safety of autonomous driving systems. While existing techniques employ camera images and onboard sensors to generate vectorized high…
Parareal algorithm via Chebyshev-Gauss spectral collocation method
Quan Zhou, Yicheng Liu, Shu-Lin Wu
We present the Parareal-CG algorithm for time-dependent differential equations in this work. The algorithm is a parallel in time iteration algorithm utilizes Chebyshev-Gauss spectr…
Neural Map Prior for Autonomous Driving
Xuan Xiong, Yicheng Liu, Tianyuan Yuan +3
High-definition (HD) semantic maps are crucial in enabling autonomous vehicles to navigate urban environments. The traditional method of creating offline HD maps involves labor-int…
CBLab: Supporting the Training of Large-scale Traffic Control Policies with Scalable Traffic Simulation
Chumeng Liang, Zherui Huang, Yicheng Liu +7
Traffic simulation provides interactive data for the optimization of traffic control policies. However, existing traffic simulators are limited by their lack of scalability and sho…
VectorMapNet: End-to-end Vectorized HD Map Learning
Yicheng Liu, Tianyuan Yuan, Yue Wang +2
Autonomous driving systems require High-Definition (HD) semantic maps to navigate around urban roads. Existing solutions approach the semantic mapping problem by offline manual ann…
Multimodal Motion Prediction with Stacked Transformers
Yicheng Liu, Jinghuai Zhang, Liangji Fang +2
Predicting multiple plausible future trajectories of the nearby vehicles is crucial for the safety of autonomous driving. Recent motion prediction approaches attempt to achieve suc…