1 citations · 1 across the 6 of their papers we have counts for
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DriveVGGT: Calibration-Constrained Visual Geometry Transformers for Multi-Camera Autonomous Driving
Xiaosong Jia, Yanhao Liu, Yu Hong +5
Feed-forward reconstruction has been progressed rapidly, with the Visual Geometry Grounded Transformer (VGGT) being a notable baseline. However, directly applying VGGT to autonomou…
LaGen: Towards Autoregressive LiDAR Scene Generation
Sizhuo Zhou, Xiaosong Jia, Fanrui Zhang +7
Generative world models for autonomous driving (AD) are of great value in applications such as data augmentation, closed-loop simulation, and safety-critical scenario evaluation. U…
InstaInpaint: Instant 3D-Scene Inpainting with Masked Large Reconstruction Model
Junqi You, Chieh Hubert Lin, Weijie Lyu +2
Recent advances in 3D scene reconstruction enable real-time viewing in virtual and augmented reality. To support interactive operations for better immersiveness, such as moving or…
DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Driving
Xiaosong Jia, Junqi You, Zhiyuan Zhang +1
End-to-end autonomous driving (E2E-AD) has emerged as a trend in the field of autonomous driving, promising a data-driven, scalable approach to system design. However, existing E2E…