JST: Joint Self-training for Unsupervised Domain Adaptation on 2D&3D Object Detection
Guangyao Ding,Meiying Zhang,E Li,Qi Hao,Guangyao Ding,Meiying Zhang,E Li,Qi Hao
2D&3D object detection always suffers from a dramatic performance drop when transferring the model trained in the source domain to the target domain due to various domain shifts. In this paper, we propose a Joint Self-Training (JST) framework to improve 2D image and 3D point cloud detectors with aligned outputs simultaneously during the transferring. The proposed framework contains three novelties...
