Automated driving systems (ADSs) promise a safe, comfortable and efficient driving
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …

Autonomous vehicles were experiencing rapid development in the past few years. However,
achieving full autonomy is not a trivial task, due to the nature of the complex and dynamic …

We propose 3DETR, an end-to-end Transformer based object detection model for 3D point
clouds. Compared to existing detection methods that employ a number of 3D-specific …

In this work, we present FFB6D, a full flow bidirectional fusion network designed for 6D pose
estimation from a single RGBD image. Our key insight is that appearance information in the …

The rapid progress in 3D scene understanding has come with growing demand for data;
however, collecting and annotating 3D scenes (eg point clouds) are notoriously hard. For …

3D object detection from LiDAR point cloud is a challenging problem in 3D scene
understanding and has many practical applications. In this paper, we extend our preliminary …

Current 3D object detection methods are heavily influenced by 2D detectors. In order to
leverage architectures in 2D detectors, they often convert 3D point clouds to regular grids …

A key technical challenge in performing 6D object pose estimation from RGB-D image is to
fully leverage the two complementary data sources. Prior works either extract information …

In this paper, we propose a novel 3D object detector that can exploit both LIDAR as well as
cameras to perform very accurate localization. Towards this goal, we design an end-to-end …

The goal of this paper is to estimate the 6D pose and dimensions of unseen object instances
in an RGB-D image. Contrary to" instance-level" 6D pose estimation tasks, our problem …