2 citations · 5 across the 15 of their papers we have counts for
6 papers · 2 filters
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…
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…
OE-BevSeg: An Object Informed and Environment Aware Multimodal Framework for Bird's-eye-view Vehicle Semantic Segmentation
Jian Sun, Yuqi Dai, Chi-Man Vong +5
Bird's-eye-view (BEV) semantic segmentation is becoming crucial in autonomous driving systems. It realizes ego-vehicle surrounding environment perception by projecting 2D multi-vie…
Neural Radiance Field in Autonomous Driving: A Survey
Lei He, Leheng Li, Wenchao Sun +5
Neural Radiance Field (NeRF) has garnered significant attention from both academia and industry due to its intrinsic advantages, particularly its implicit representation and novel…