3 citations · 6 across the 12 of their papers we have counts for
5 papers · 1 filter
CoBEVMoE: Heterogeneity-aware Feature Fusion with Dynamic Mixture-of-Experts for Collaborative Perception
Lingzhao Kong, Jiacheng Lin, Siyu Li +3
Collaborative perception aims to extend sensing coverage and improve perception accuracy by sharing information among multiple agents. However, due to differences in viewpoints and…
Hallucinating 360°: Panoramic Street-View Generation via Local Scenes Diffusion and Probabilistic Prompting
Fei Teng, Kai Luo, Sheng Wu +6
Panoramic perception holds significant potential for autonomous driving, enabling vehicles to acquire a comprehensive 360° surround view in a single shot. However, autonomous drivi…
NRSeg: Noise-Resilient Learning for BEV Semantic Segmentation via Driving World Models
Siyu Li, Fei Teng, Yihong Cao +3
Birds' Eye View (BEV) semantic segmentation is an indispensable perception task in end-to-end autonomous driving systems. Unsupervised and semi-supervised learning for BEV tasks, a…
HierDAMap: Towards Universal Domain Adaptive BEV Mapping via Hierarchical Perspective Priors
Siyu Li, Yihong Cao, Hao Shi +4
The exploration of Bird's-Eye View (BEV) mapping technology has driven significant innovation in visual perception technology for autonomous driving. BEV mapping models need to be…
L2G-Map: Local-to-Global Mapping via Hierarchical Diffusion Refinement and Elliptical Bayesian Fusion
Siyu Li, Xinying Hong, Fei Teng +5
Offline high-definition maps provide essential geometric and topological priors for autonomous driving systems. Pure-vision solutions have become the predominant paradigm for offli…