Search Results for author:
Found 4 papers, 3 papers with code
Neural Object Learning for 6D Pose Estimation Using a Few Cluttered Images
Recent methods for 6D pose estimation of objects assume either textured 3D models or real images that cover the entire range of target poses.
Unsupervised Domain Adaptation through Inter-modal Rotation for RGB-D Object Recognition
Unsupervised Domain Adaptation (DA) exploits the supervision of a label-rich source dataset to make predictions on an unlabeled target dataset by aligning the two data distributions.
DGCM-Net: Dense Geometrical Correspondence Matching Network for Incremental Experience-based Robotic Grasping
This article presents a method for grasping novel objects by learning from experience.
Robotics
Pix2Pose: Pixel-Wise Coordinate Regression of Objects for 6D Pose Estimation
Estimating the 6D pose of objects using only RGB images remains challenging because of problems such as occlusion and symmetries.
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6D Pose Estimation using RGB
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