3 papers
cs.CV2020
Neural Object Learning for 6D Pose Estimation Using a Few Cluttered Images
Kiru Park, Timothy Patten, Markus Vincze
Recent methods for 6D pose estimation of objects assume either textured 3D models or real images that cover the entire range of target poses. However, it is difficult to obtain tex…
cs.RO2020
DGCM-Net: Dense Geometrical Correspondence Matching Network for Incremental Experience-based Robotic Grasping
Timothy Patten, Kiru Park, Markus Vincze
This article presents a method for grasping novel objects by learning from experience. Successful attempts are remembered and then used to guide future grasps such that more reliab…
cs.CV2019
Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation
Kiru Park, Timothy Patten, Markus Vincze
Estimating the 6D pose of objects using only RGB images remains challenging because of problems such as occlusion and symmetries. It is also difficult to construct 3D models with p…