8 papers · 1 filter
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…
WPT: World-to-Policy Transfer via Online World Model Distillation
Guangfeng Jiang, Yueru Luo, Jun Liu +6
Recent years have witnessed remarkable progress in world models, which primarily aim to capture the spatio-temporal correlations between an agent's actions and the evolving environ…
ALISE: Annotation-Free LiDAR Instance Segmentation for Autonomous Driving
Yongxuan Lyu, Guangfeng Jiang, Hongsi Liu +1
The manual annotation of outdoor LiDAR point clouds for instance segmentation is extremely costly and time-consuming. Current methods attempt to reduce this burden but still rely o…
MLF-4DRCNet: Multi-Level Fusion with 4D Radar and Camera for 3D Object Detection in Autonomous Driving
Yuzhi Wu, Li Xiao, Jun Liu +2
The emerging 4D millimeter-wave radar, measuring the range, azimuth, elevation, and Doppler velocity of objects, is recognized for its cost-effectiveness and robustness in autonomo…
You Only Click Once: Single Point Weakly Supervised 3D Instance Segmentation for Autonomous Driving
Guangfeng Jiang, Jun Liu, Yongxuan Lv +5
Outdoor LiDAR point cloud 3D instance segmentation is a crucial task in autonomous driving. However, it requires laborious human efforts to annotate the point cloud for training a…
Mask-RadarNet: Enhancing Transformer With Spatial-Temporal Semantic Context for Radar Object Detection in Autonomous Driving
Yuzhi Wu, Jun Liu, Guangfeng Jiang +2
As a cost-effective and robust technology, automotive radar has seen steady improvement during the last years, making it an appealing complement to commonly used sensors like camer…