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 …

3D object detection from images, one of the fundamental and challenging problems in
autonomous driving, has received increasing attention from both industry and academia in …

Recent progress in 3D object detection from single images leverages monocular depth
estimation as a way to produce 3D pointclouds, turning cameras into pseudo-lidar sensors …

In this work, we propose an efficient and accurate monocular 3D detection framework in
single shot. Most successful 3D detectors take the projection constraint from the 3D …

Abstract 3D object detection from a single image without LiDAR is a challenging task due to
the lack of accurate depth information. Conventional 2D convolutions are unsuitable for this …

The recently proposed pseudo-LiDAR based 3D detectors greatly improve the benchmark of
monocular/stereo 3D detection task. However, the underlying mechanism remains obscure …

The objective of this paper is to learn context-and depth-aware feature representation to
solve the problem of monocular 3D object detection. We make following contributions:(i) …

Estimating the 3D position and orientation of objects in the environment with a single RGB
camera is a critical and challenging task for low-cost urban autonomous driving and mobile …

Monocular 3D object detection is an essential task in autonomous driving. However, most
current methods consider each 3D object in the scene as an independent training sample …

Fully automated vehicles collect information about their road environments to adjust their
driving actions, such as braking and slowing down. The development of artificial intelligence …