5 citations · 10 across the 14 of their papers we have counts for
8 papers · 1 filter
RS2AD-LiDAR: End-to-End Autonomous Driving LiDAR Data Generation from Roadside Sensor Observations
Runyi Huang, Ni Ding, Ruidan Xing +3
End-to-end autonomous driving solutions, which directly process multimodal sensory data and output fine-grained control commands, have gradually become a mainstream direction with…
Unveiling the Black Box: Independent Functional Module Evaluation for Bird's-Eye-View Perception Model
Ludan Zhang, Xiaokang Ding, Yuqi Dai +2
End-to-end models are emerging as the mainstream in autonomous driving perception. However, the inability to meticulously deconstruct their internal mechanisms results in diminishe…
Vision-Driven 2D Supervised Fine-Tuning Framework for Bird's Eye View Perception
Lei He, Qiaoyi Wang, Honglin Sun +5
Visual bird's eye view (BEV) perception, due to its excellent perceptual capabilities, is progressively replacing costly LiDAR-based perception systems, especially in the realm of…
GS-Net: Heterogeneous Vehicle Data Reuse via Generalizable Plug-and-Play 3DGS Module
Yichen Zhang, Zihan Wang, Jiali Han +5
End-to-end autonomous driving is increasingly data-driven, yet data reuse across vehicles remains limited. Each new vehicle often requires additional data collection and retraining…
Local Map Construction with SDMap: A Comprehensive Survey
Jiaqi Li, Pingfan Jia, Jiaxing Chen +3
Local map construction is a vital component of intelligent driving perception, offering necessary reference for vehicle positioning and planning. Standard Definition map (SDMap), k…
Hierarchical and Decoupled BEV Perception Learning Framework for Autonomous Driving
Yuqi Dai, Jian Sun, Shengbo Eben Li +4
Perception is essential for autonomous driving system. Recent approaches based on Bird's-eye-view (BEV) and deep learning have made significant progress. However, there exists chal…