Point cloud learning has lately attracted increasing attention due to its wide applications in
many areas, such as computer vision, autonomous driving, and robotics. As a dominating …

Image instance segmentation involves labeling pixels of images with classes and instances,
which is one of the pivotal technologies in many domains, such as natural scenes …

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 …

Instance segmentation is an important task for scene understanding. Compared to the fully-
developed 2D, 3D instance segmentation for point clouds have much room to improve. In …

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 …

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 …

Instance segmentation on point clouds is a fundamental task in 3D scene perception. In this
work, we propose a concise clustering-based framework named HAIS, which makes full use …

Pretraining on large labeled datasets is a prerequisite to achieve good performance in many
computer vision tasks like image recognition, video understanding etc. However, pretraining …