6 papers
UNIVERSE: Unified Video Action Models for Autonomous Driving with Flexible Mask-Modulated Modality Generation
Mengmeng Liu, Diankun Zhang, Jiuming Liu +7
World Action Models (WAMs) have shown strong potential for improving action generalization in autonomous driving by using future video prediction as dense supervision for scene dyn…
DriveVA: Video Action Models are Zero-Shot Drivers
Mengmeng Liu, Diankun Zhang, Jiuming Liu +7
Generalization is a central challenge in autonomous driving, as real-world deployment requires robust performance under unseen scenarios, sensor domains, and environmental conditio…
Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends
Jiuming Liu, Chaojun Ni, Mengmeng Liu +7
With rapid development of large language models and diffusion-based content generation, world modeling has attracted increasing research attention, benefiting various downstream do…
RegFormer++: An Efficient Large-Scale 3D LiDAR Point Registration Network with Projection-Aware 2D Transformer
Jiuming Liu, Guangming Wang, Zhe Liu +7
Although point cloud registration has achieved remarkable advances in object-level and indoor scenes, large-scale LiDAR registration methods has been rarely explored before. Challe…
4DSTR: Advancing Generative 4D Gaussians with Spatial-Temporal Rectification for High-Quality and Consistent 4D Generation
Mengmeng Liu, Jiuming Liu, Yunpeng Zhang +4
Remarkable advances in recent 2D image and 3D shape generation have induced a significant focus on dynamic 4D content generation. However, previous 4D generation methods commonly s…
DVLO4D: Deep Visual-Lidar Odometry with Sparse Spatial-temporal Fusion
Mengmeng Liu, Michael Ying Yang, Jiuming Liu +5
Visual-LiDAR odometry is a critical component for autonomous system localization, yet achieving high accuracy and strong robustness remains a challenge. Traditional approaches comm…