With recent developments, the performance of automotive radar has improved significantly.
The next generation of 4D radar can achieve imaging capability in the form of high …

LiDAR is a commonly used sensor for autonomous driving to make accurate, robust, and fast
decision-making when driving. The sensor is used in the perception system, especially …

Driven by improved architectures and better representation learning frameworks, the field of
visual recognition has enjoyed rapid modernization and performance boost in the early …

LiDAR-based 3D point cloud recognition has benefited various applications. Without
specially considering the LiDAR point distribution, most current methods suffer from …

Abstract 3D point cloud segmentation has made tremendous progress in recent years. Most
current methods focus on aggregating local features, but fail to directly model long-range …

Modern 3D semantic instance segmentation approaches predominantly rely on specialized
voting mechanisms followed by carefully designed geometric clustering techniques. Building …

We study the problem of efficient object detection of 3D LiDAR point clouds. To reduce the
memory and computational cost, existing point-based pipelines usually adopt task-agnostic …

In this work, we present a unified framework for multi-modality 3D object detection, named
UVTR. The proposed method aims to unify multi-modality representations in the voxel space …

Designing an efficient yet deployment-friendly 3D backbone to handle sparse point clouds is
a fundamental problem in 3D perception. Compared with the customized sparse …

FlowFormer introduces a transformer architecture into optical flow estimation and achieves
state-of-the-art performance. The core component of FlowFormer is the transformer-based …