5 papers · 1 filter
ProjFormer: Point Cloud Completion via Geometric-Projective Transformer and Cross-Modal Semantic Constraints
Sheng Liu, Meng Wang, Ruihui Li +3
Point cloud completion is inherently ill-posed due to severe sparsity and ambiguity in partial observations. Existing multi-view methods alleviate this by incorporating 2D semantic…
RayLift: Lifting Complementary Ray-Wise Evidence with 3D Geometry Priors for Semantic Scene Completion
Meng Wang, Hongxia Yu, Wenzhe He +4
Camera-based 3D semantic scene completion (SSC) provides comprehensive scene understanding for autonomous driving and robotics. However, existing methods often treat stereo depth e…
LiNeXt: Revisiting LiDAR Completion with Efficient Non-Diffusion Architectures
Wenzhe He, Xiaojun Chen, Ruiqi Wang +5
3D LiDAR scene completion from point clouds is a fundamental component of perception systems in autonomous vehicles. Previous methods have predominantly employed diffusion models f…
Self-Supervised Point Cloud Completion based on Multi-View Augmentations of Single Partial Point Cloud
Jingjing Lu, Huilong Pi, Yunchuan Qin +2
Point cloud completion aims to reconstruct complete shapes from partial observations. Although current methods have achieved remarkable performance, they still have some limitation…
VLScene: Vision-Language Guidance Distillation for Camera-Based 3D Semantic Scene Completion
Meng Wang, Huilong Pi, Ruihui Li +3
Camera-based 3D semantic scene completion (SSC) provides dense geometric and semantic perception for autonomous driving. However, images provide limited information making the mode…