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 …

摘要视觉目标检测旨在定位和识别图像中存在的物体, 属于计算机视觉领域的经典任务之一,
也是许多计算机视觉任务的前提与基础, 在自动驾驶, 视频监控等领域具有重要的应用价值 …

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

The transportation detection of long-distance small objects has low accuracy. In this work,
we propose DMF, which is based on disparity depths. We map different disparity regions to …

Monocular 3D object detection aims to localize 3D bounding boxes in an input single 2D
image. It is a highly challenging problem and remains open, especially when no extra …

Stereo-based 3D detection aims at detecting 3D object bounding boxes from stereo images
using intermediate depth maps or implicit 3D geometry representations, which provides a …

Perceiving 3D objects from monocular inputs is crucial for robotic systems, given its
economy compared to multi-sensor settings. It is notably difficult as a single image can not …

Reliable and accurate 3D object detection is a necessity for safe autonomous driving.
Although LiDAR sensors can provide accurate 3D point cloud estimates of the environment …

An accurate and robust perception system is key to understanding the driving environment
of autonomous driving and robots. Autonomous driving needs 3-D information about objects …