7 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…
MU-GeNeRF: Multi-view Uncertainty-guided Generalizable Neural Radiance Fields for Distractor-aware Scene
Wenjie Mu, Zhan Li, Chuanzhou Su +8
Generalizable Neural Radiance Fields (GeNeRFs) enable high-quality scene reconstruction from sparse views and can generalize to unseen scenes. However, in real-world settings, tran…
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…
R2LDM: An Efficient 4D Radar Super-Resolution Framework Leveraging Diffusion Model
Boyuan Zheng, Shouyi Lu, Renbo Huang +5
We introduce R2LDM, an innovative approach for generating dense and accurate 4D radar point clouds, guided by corresponding LiDAR point clouds. Instead of utilizing range images or…
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…