12 citations · 30 across the 10 of their papers we have counts for
11 papers
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…
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…
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…
BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction
Zikang Zhou, Haibo Hu, Xinhong Chen +6
Simulating realistic behaviors of traffic agents is pivotal for efficiently validating the safety of autonomous driving systems. Existing data-driven simulators primarily use an en…
Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Driving
Yang Lou, Qun Song, Qian Xu +2
Multi-modal fusion has shown initial promising results for object detection of autonomous driving perception. However, many existing fusion schemes do not consider the quality of e…
QCNeXt: A Next-Generation Framework For Joint Multi-Agent Trajectory Prediction
Zikang Zhou, Zihao Wen, Jianping Wang +2
Estimating the joint distribution of on-road agents' future trajectories is essential for autonomous driving. In this technical report, we propose a next-generation framework for j…
TOFG: A Unified and Fine-Grained Environment Representation in Autonomous Driving
Zihao Wen, Yifan Zhang, Xinhong Chen +1
In autonomous driving, an accurate understanding of environment, e.g., the vehicle-to-vehicle and vehicle-to-lane interactions, plays a critical role in many driving tasks such as…
Improving the Generalizability of Trajectory Prediction Models with Frenet-Based Domain Normalization
Luyao Ye, Zikang Zhou, Jianping Wang
Predicting the future trajectories of nearby objects plays a pivotal role in Robotics and Automation such as autonomous driving. While learning-based trajectory prediction methods…