6D Object Pose Regression via Supervised Learning on Point Clouds
Ge Gao,Mikko Lauri,Yulong Wang,Xiaolin Hu,Jianwei Zhang,Simone Frintrop,Ge Gao,Mikko Lauri,Yulong Wang,Xiaolin Hu,Jianwei Zhang,Simone Frintrop
This paper addresses the task of estimating the 6 degrees of freedom pose of a known 3D object from depth information represented by a point cloud. Deep features learned by convolutional neural networks from color information have been the dominant features to be used for inferring object poses, while depth information receives much less attention. However, depth information contains rich geometri...
