The grid-centric perception is a crucial field for mobile robot perception and navigation.
Nonetheless, the grid-centric perception is less prevalent than object-centric perception as …

In recent years, Simultaneous Localization and Map** (SLAM) systems have shown
significant performance, accuracy, and efficiency gains, especially when Neural Radiance …

Nowadays, autonomous cars can drive smoothly in ordinary cases, and it is widely
recognized that realistic sensor simulation will play a critical role in solving remaining corner …

Computer vision techniques play a central role in the perception stack of autonomous
vehicles. Such methods are employed to perceive the vehicle surroundings given sensor …

Semantic scene completion also known as semantic occupancy prediction can provide
dense geometric and semantic information for autonomous vehicles which attracts the …

Abstract 3D correspondence ie a pair of 3D points is a fundamental concept in computer
vision. A set of 3D correspondences when equipped with compatibility edges forms a …

Monocular Semantic Occupancy Prediction aims to infer the complete 3D geometry and
semantic information of scenes from only 2D images. It has garnered significant attention …

Current point cloud completion research mainly utilizes the global shape representation and
local features to recover the missing regions of 3D shape for the partial point cloud …

Keypoint-based representation has proven advantageous in various visual and robotic
tasks. However, the existing 2D and 3D methods for detecting keypoints mainly rely on …

Semantic scene completion (SSC) aims to predict the semantic occupancy of each voxel in
the entire 3D scene from limited observations, which is an emerging and critical task for …