False Positive Sampling-based Data Augmentation for Enhanced 3D Object Detection Accuracy

arXiv:2403.02639v1 Announce Type: cross
Abstract: Recent studies have focused on enhancing the performance of 3D object detection models. Among various approaches, ground-truth sampling has been proposed as an augmentation technique to address the challenges posed by limited ground-truth data. However, an inherent issue with ground-truth sampling is its tendency to increase false positives. Therefore, this study aims to overcome the limitations of ground-truth sampling and improve the performance of 3D object detection models by developing a new augmentation technique called …

3d object 3d object detection abstract accuracy arxiv augmentation challenges cs.cv cs.lg data detection false ground-truth issue object performance positive sampling studies truth type