Pseudo Label Refinery for Unsupervised Domain Adaptation on
Cross-dataset 3D Object Detection
Pseudo Label Refinery for Unsupervised Domain Adaptation on
Cross-dataset 3D Object Detection
Recent self-training techniques have shown notable improvements in unsupervised domain adaptation for 3D object detection (3D UDA). These techniques typically select pseudo labels, i.e., 3D boxes, to supervise models for the target domain. However, this selection process inevitably introduces unreliable 3D boxes, in which 3D points cannot be definitively assigned …