6 papers
Geometry Reinforced Efficient Attention Tuning Equipped with Normals for Robust Stereo Matching
Jiahao Li, Xinhong Chen, Zhengmin Jiang +3
Despite remarkable advances in image-driven stereo matching over the past decade, Synthetic-to-Realistic ZeroShot (Syn-to-Real) generalization remains an open challenge. This subop…
Mode-as-Sequence: Translating Multimodal Motion Prediction into Unified Sequential Mode Modeling
Zikang Zhou, Haibo Hu, Xinhong Chen +5
Multimodal motion forecasting is inherently under-supervised: each training scene provides only one realized future, yet multiple plausible futures exist. This sparse supervision o…
One World, Dual Timeline: Decoupled Spatio-Temporal Gaussian Scene Graph for 4D Cooperative Driving Reconstruction
Yulong Chen, Xiaoyun Dong, Haoyu Zhang +6
Reconstructing dynamic scenes from Vehicle-to-Infrastructure Cooperative Autonomous Driving (VICAD) data is fundamentally complicated by temporal asynchrony: vehicle and infrastruc…
SATMapTR: Satellite Image Enhanced Online HD Map Construction
Bingyuan Huang, Guanyi Zhao, Qian Xu +3
High-definition (HD) maps are evolving from pre-annotated to real-time construction to better support autonomous driving in diverse scenarios. However, this process is hindered by…
RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning
Jiacheng Zuo, Haibo Hu, Zikang Zhou +6
In the pursuit of robust autonomous driving systems, models trained on real-world datasets often struggle to adapt to new environments, particularly when confronted with corner cas…
ModeSeq: Taming Sparse Multimodal Motion Prediction with Sequential Mode Modeling
Zikang Zhou, Hengjian Zhou, Haibo Hu +4
Anticipating the multimodality of future events lays the foundation for safe autonomous driving. However, multimodal motion prediction for traffic agents has been clouded by the la…