3 citations · 8 across the 5 of their papers we have counts for
5 papers
Boosting Monocular 3D Object Detection with Object-Centric Auxiliary Depth Supervision
Youngseok Kim, Sanmin Kim, Sangmin Sim +2
Recent advances in monocular 3D detection leverage a depth estimation network explicitly as an intermediate stage of the 3D detection network. Depth map approaches yield more accur…
D-Align: Dual Query Co-attention Network for 3D Object Detection Based on Multi-frame Point Cloud Sequence
Junhyung Lee, Junho Koh, Youngwoo Lee +1
LiDAR sensors are widely used for 3D object detection in various mobile robotics applications. LiDAR sensors continuously generate point cloud data in real-time. Conventional 3D ob…
CRAFT: Camera-Radar 3D Object Detection with Spatio-Contextual Fusion Transformer
Youngseok Kim, Sanmin Kim, Jun Won Choi +1
Camera and radar sensors have significant advantages in cost, reliability, and maintenance compared to LiDAR. Existing fusion methods often fuse the outputs of single modalities at…
Joint 3D Object Detection and Tracking Using Spatio-Temporal Representation of Camera Image and LiDAR Point Clouds
Junho Koh, Jaekyum Kim, Jinhyuk Yoo +3
In this paper, we propose a new joint object detection and tracking (JoDT) framework for 3D object detection and tracking based on camera and LiDAR sensors. The proposed method, re…
Greedy Sparse Signal Recovery with Tree Pruning
Jaeseok Lee, Suhyuk Kwon, Jun Won Choi +1
Recently, greedy algorithm has received much attention as a cost-effective means to reconstruct the sparse signals from compressed measurements. Much of previous work has focused o…