6 papers
Signal Structure-Aware Gaussian Splatting for Large-Scale Scene Reconstruction
Weiyi Xue, Fan Lu, Chi Zhang +6
3D Gaussian Splatting has demonstrated remarkable potential in novel view synthesis. In contrast to small-scale scenes, large-scale scenes inevitably contain sparsely observed regi…
PointForward: Feedforward Driving Reconstruction through Point-Aligned Representations
Cheng Chi, Xianqi Wang, Hongcheng Luo +9
High-fidelity reconstruction of driving scenes is crucial for autonomous driving. While recent feedforward 3D Gaussian Splatting (3DGS) methods enable fast reconstruction, their pe…
MTA-RL: Robust Urban Driving via Multi-modal Transformer-based 3D Affordances and Reinforcement Learning
Guangli Chen, Dianzhao Li, Wenjian Zhong +2
Robust urban autonomous driving requires reliable 3D scene understanding and stable decision-making under dense interactions. However, existing end-to-end models lack interpretabil…
LiDARDraft: Generating LiDAR Point Cloud from Versatile Inputs
Haiyun Wei, Fan Lu, Yunwei Zhu +7
Generating realistic and diverse LiDAR point clouds is crucial for autonomous driving simulation. Although previous methods achieve LiDAR point cloud generation from user inputs, t…
UrbanCraft: Urban View Extrapolation via Hierarchical Sem-Geometric Priors
Tianhang Wang, Fan Lu, Sanqing Qu +5
Existing neural rendering-based urban scene reconstruction methods mainly focus on the Interpolated View Synthesis (IVS) setting that synthesizes from views close to training camer…
RCDN: Towards Robust Camera-Insensitivity Collaborative Perception via Dynamic Feature-based 3D Neural Modeling
Tianhang Wang, Fan Lu, Zehan Zheng +3
Collaborative perception is dedicated to tackling the constraints of single-agent perception, such as occlusions, based on the multiple agents' multi-view sensor inputs. However, m…