LiDAR and camera are two important sensors for 3D object detection in autonomous driving.
Despite the increasing popularity of sensor fusion in this field, the robustness against inferior …

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 …

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 …

Camera and LiDAR sensor modalities provide complementary appearance and geometric
information useful for detecting 3D objects for autonomous vehicle applications. However …

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

Fusing the camera and LiDAR information has become a de-facto standard for 3D object
detection tasks. Current methods rely on point clouds from the LiDAR sensor as queries to …

LiDAR and camera are two common sensors to collect data in time for 3D object detection
under the autonomous driving context. Though the complementary information across …

Abstract 3D object detectors usually rely on hand-crafted proxies, eg, anchors or centers,
and translate well-studied 2D frameworks to 3D. Thus, sparse voxel features need to be …

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

Camera and LiDAR are two complementary sensors for 3D object detection in the
autonomous driving context. Camera provides rich texture and color cues while LiDAR …