70 citations · 108 across the 6 of their papers we have counts for
6 papers
MGTANet: Encoding Sequential LiDAR Points Using Long Short-Term Motion-Guided Temporal Attention for 3D Object Detection
Junho Koh, Junhyung Lee, Youngwoo Lee +2
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…
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…
Joint Representation of Temporal Image Sequences and Object Motion for Video Object Detection
Junho Koh, Jaekyum Kim, Younji Shin +3
In this paper, we propose a new video object detector (VoD) method referred to as temporal feature aggregation and motion-aware VoD (TM-VoD), which produces a joint representation…
Robust Deep Multi-modal Learning Based on Gated Information Fusion Network
Jaekyum Kim, Junho Koh, Yecheol Kim +3
The goal of multi-modal learning is to use complimentary information on the relevant task provided by the multiple modalities to achieve reliable and robust performance. Recently,…
Probabilistic Vehicle Trajectory Prediction over Occupancy Grid Map via Recurrent Neural Network
ByeoungDo Kim, Chang Mook Kang, Seung Hi Lee +4
In this paper, we propose an efficient vehicle trajectory prediction framework based on recurrent neural network. Basically, the characteristic of the vehicle's trajectory is diffe…
Autonomous Braking System via Deep Reinforcement Learning
Hyunmin Chae, Chang Mook Kang, ByeoungDo Kim +3
In this paper, we propose a new autonomous braking system based on deep reinforcement learning. The proposed autonomous braking system automatically decides whether to apply the br…