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Markus Suchi

2 accepted papers

2023

3D-DAT: 3D-Dataset Annotation Toolkit for Robotic Vision

ICRA 2023poster

Robots operating in the real world are expected to detect, classify, segment, and estimate the pose of objects to accomplish their task. Modern approaches using deep learning not only require large volumes of data but also pixel-accurate annotations in order to evaluate the performance and therefore…

Cited by 13SourcecodeScholar
2019

EasyLabel: A Semi-Automatic Pixel-wise Object Annotation Tool for Creating Robotic RGB-D Datasets

ICRA 2019poster

Developing robot perception systems for recognizing objects in the real world requires computer vision algorithms to be carefully scrutinized with respect to the expected operating domain. This demands large quantities of ground truth data to rigorously evaluate the performance of algorithms. This p…

Cited by 126SourceScholar