Mattias Hansson

UADA3D: Unsupervised Adversarial Domain Adaptation for 3D Object Detection With Sparse LiDAR and Large Domain Gaps

In this study, we address a gap in existing unsupervised domain adaptation approaches on LiDAR-based 3D object detection, which have predominantly concentrated on adapting between established, high-density autonomous driving datasets. We focus on sparser point clouds, capturing scenarios from differ