LiDAR-Camera fusion-based 3D detection is a critical task for automatic driving. In recent
years, many LiDAR-Camera fusion approaches sprung up and gained promising …

Lidars and cameras are critical sensors that provide complementary information for 3D
detection in autonomous driving. While prevalent multi-modal methods simply decorate raw …

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 …

3D object detection based on LiDAR-camera fusion is becoming an emerging research
theme for autonomous driving. However, it has been surprisingly difficult to effectively fuse …

LiDAR-camera fusion methods have shown impressive performance in 3D object detection.
Recent advanced multi-modal methods mainly perform global fusion, where image features …

In autonomous driving, the robust and accurate perceptions of the environment is a
fundamental and challenging task. Resorting to the advancing of different sensors such as …

In this paper, we propose a new deep architecture for fusing camera and LiDAR sensors for
3D object detection. Because the camera and LiDAR sensor signals have different …

We propose LiRaFusion to tackle LiDAR-radar fusion for 3D object detection to fill the
performance gap of existing LiDAR-radar detectors. To improve the feature extraction …

To achieve autonomous driving, developing 3D detection fusion methods, which aim to fuse
the camera and LiDAR information, has draw great research interest in recent years. As a …

Accurate and reliable perception systems are essential for autonomous driving and robotics.
To achieve this, 3D object detection with multi-sensors is necessary. Existing 3D detectors …