Youngwoo Lee — accepted AI-conference papers

2023

D-Align: Dual Query Co-attention Network for 3D Object Detection Based on Multi-frame Point Cloud Sequence

Junhyung Lee, Junho Koh, Youngwoo Lee, Jun Won Choi

ICRA 2023poster

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 object detectors detect objects using a set of points acquired over a fixed duration. However, recent studies have shown t…

Cited by 14 Source ↗code ↗Scholar ↗

2023

MGTANet: Encoding Sequential LiDAR Points Using Long Short-Term Motion-Guided Temporal Attention for 3D Object Detection

Junho Koh, Junhyung Lee, Youngwoo Lee, Jaekyum Kim, Jun Won Choi

AAAI 2023technical

Most scanning LiDAR sensors generate a sequence of point clouds in real-time. While conventional 3D object detectors use a set of unordered LiDAR points acquired over a fixed time interval, recent studies have revealed that substantial performance improvement can be achieved by exploiting the spatio…

Cited by 29 Source ↗PDF ↗code ↗Scholar ↗