Self-Supervised Learning of Object Segmentation from Unlabeled RGB-D Videos
Shiyang Lu,Yunfu Deng,Abdeslam Boularias,Kostas Bekris,Shiyang Lu,Yunfu Deng,Abdeslam Boularias,Kostas Bekris
This work proposes a self-supervised learning system for segmenting rigid objects in RGB images. The proposed pipeline is trained on unlabeled RGB-D videos of static objects, which can be captured with a camera carried by a mobile robot. A key feature of the self-supervised training process is a graph-matching algorithm that operates on the over-segmentation output of the point cloud that is recon...
