7 citations · 16 across the 18 of their papers we have counts for
Showing 2025 · cs.CVShow all
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cs.CV2025
DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving
Ziying Song, Lin Liu, Hongyu Pan +7
Most end-to-end autonomous driving methods rely on imitation learning from single expert demonstrations, often leading to conservative and homogeneous behaviors that limit generali…
cs.CV2025
Collaborative Perception Datasets for Autonomous Driving: A Review
Naibang Wang, Deyong Shang, Yan Gong +6
Collaborative perception has attracted growing interest from academia and industry due to its potential to enhance perception accuracy, safety, and robustness in autonomous driving…
cs.CV2025
Fully Unified Motion Planning for End-to-End Autonomous Driving
Lin Liu, Caiyan Jia, Ziying Song +6
Current end-to-end autonomous driving methods typically learn only from expert planning data collected from a single ego vehicle, severely limiting the diversity of learnable drivi…