26 citations · 49 across the 8 of their papers we have counts for
4 papers · 1 filter
R-Pred: Two-Stage Motion Prediction Via Tube-Query Attention-Based Trajectory Refinement
Sehwan Choi, Jungho Kim, Junyong Yun +1
Predicting the future motion of dynamic agents is of paramount importance to ensuring safety and assessing risks in motion planning for autonomous robots. In this study, we propose…
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…
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…
Diverse Multiple Trajectory Prediction Using a Two-stage Prediction Network Trained with Lane Loss
Sanmin Kim, Hyeongseok Jeon, Junwon Choi +1
Prior arts in the field of motion predictions for autonomous driving tend to focus on finding a trajectory that is close to the ground truth trajectory. Such problem formulations a…