Autonomous driving, in recent years, has been receiving increasing attention for its potential
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …

LiDAR-based 3D object detection for autonomous driving has recently drawn the attention of
both academia and industry since it relies upon a sensor that incorporates appealing …

We study the problem of efficient object detection of 3D LiDAR point clouds. To reduce the
memory and computational cost, existing point-based pipelines usually adopt task-agnostic …

We present a novel and high-performance 3D object detection framework, named
PointVoxel-RCNN (PV-RCNN), for accurate 3D object detection from point clouds. Our …

In autonomous driving, a LiDAR-based object detector should perform reliably at different
geographic locations and under various weather conditions. While recent 3D detection …

Advances in LiDAR sensors provide rich 3D data that supports 3D scene understanding.
However, due to occlusion and signal miss, LiDAR point clouds are in practice 2.5 D as they …

Generating realistic 3D worlds occupied by moving humans has many applications in
games, architecture, and synthetic data creation. But generating such scenes is expensive …

For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …

As the foundation of intelligent systems, machine vision perceives the surrounding
environment and provides a basis for decision-making. Object detection is the core task in …

DoF object pose estimation from a monocular image is challenging, and a post-refinement
procedure is generally needed for high-precision estimation. In this paper, we propose a …