6 papers
DLWM: Dual Latent World Models enable Holistic Gaussian-centric Pre-training in Autonomous Driving
Yiyao Zhu, Ying Xue, Haiming Zhang +8
Vision-based autonomous driving has gained much attention due to its low costs and excellent performance. Compared with dense BEV (Bird's Eye View) or sparse query models, Gaussian…
VG3S: Visual Geometry Grounded Gaussian Splatting for Semantic Occupancy Prediction
Xiaoyang Yan, Muleilan Pei, Shaojie Shen
3D semantic occupancy prediction has become a crucial perception task for comprehensive scene understanding in autonomous driving. While recent advances have explored 3D Gaussian s…
Advancing Multi-agent Traffic Simulation via R1-Style Reinforcement Fine-Tuning
Muleilan Pei, Shaoshuai Shi, Shaojie Shen
Scalable and realistic simulation of multi-agent traffic behavior is critical for advancing autonomous driving technologies. Although existing data-driven simulators have made sign…
ST-GS: Vision-Based 3D Semantic Occupancy Prediction with Spatial-Temporal Gaussian Splatting
Xiaoyang Yan, Muleilan Pei, Shaojie Shen
3D occupancy prediction is critical for comprehensive scene understanding in vision-centric autonomous driving. Recent advances have explored utilizing 3D semantic Gaussians to mod…
Foresight in Motion: Reinforcing Trajectory Prediction with Reward Heuristics
Muleilan Pei, Shaoshuai Shi, Xuesong Chen +2
Motion forecasting for on-road traffic agents presents both a significant challenge and a critical necessity for ensuring safety in autonomous driving systems. In contrast to most…
GoIRL: Graph-Oriented Inverse Reinforcement Learning for Multimodal Trajectory Prediction
Muleilan Pei, Shaoshuai Shi, Lu Zhang +2
Trajectory prediction for surrounding agents is a challenging task in autonomous driving due to its inherent uncertainty and underlying multimodality. Unlike prevailing data-driven…