4 papers
BEV-Denoise: Learning Intrinsic Noise for Accurate Bird's-Eye-View Semantic Segmentation
Dooseop Choi, Kyounghwan An, Kyoung-Wook Min
In this paper, we present a framework dubbed \textbf{BEV-Denoise} that estimates and removes intrinsic noise from learned Bird's-Eye-View (BEV) features to achieve accurate BEV sem…
CycleBEV: Regularizing View Transformation Networks via View Cycle Consistency for Bird's-Eye-View Semantic Segmentation
Jeongbin Hong, Dooseop Choi, Taeg-Hyun An +2
Transforming image features from perspective view (PV) space to bird's-eye-view (BEV) space remains challenging in autonomous driving due to depth ambiguity and occlusion. Although…
LANet: A Lane Boundaries-Aware Approach For Robust Trajectory Prediction
Muhammad Atta ur Rahman, Dooseop Choi, KyoungWook Min
Accurate motion forecasting is critical for safe and efficient autonomous driving, enabling vehicles to predict future trajectories and make informed decisions in complex traffic s…
Progressive Query Refinement Framework for Bird's-Eye-View Semantic Segmentation from Surrounding Images
Dooseop Choi, Jungyu Kang, Taeghyun An +2
Expressing images with Multi-Resolution (MR) features has been widely adopted in many computer vision tasks. In this paper, we introduce the MR concept into Bird's-Eye-View (BEV) s…