Autonomous vehicles are becoming central for the future of mobility, supported by advances
in deep learning techniques. The performance of aself-driving system is highly dependent …

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 …

Lidar-based sensing drives current autonomous vehicles. Despite rapid progress, current
Lidar sensors still lag two decades behind traditional color cameras in terms of resolution …

Abstract We present Self-Ensembling Single-Stage object Detector (SE-SSD) for accurate
and efficient 3D object detection in outdoor point clouds. Our key focus is on exploiting both …

Three-dimensional objects are commonly represented as 3D boxes in a point-cloud. This
representation mimics the well-studied image-based 2D bounding-box detection but comes …

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

Accurate detection of obstacles in 3D is an essential task for autonomous driving and
intelligent transportation. In this work, we propose a general multimodal fusion framework …

We address the problem of 3D object detection, that is, estimating 3D object bounding boxes
from point clouds. 3D object detection methods exploit either voxel-based or point-based …

Previous works for LiDAR-based 3D object detection mainly focus on the single-frame
paradigm. In this paper, we propose to detect 3D objects by exploiting temporal information …

In this paper, we present an Intersection-over-Union (IoU) guided two-stage 3D object
detector with a voxel-to-point decoder. To preserve the necessary information from all raw …