17 citations · 21 across the 2 of their papers we have counts for
4 papers · 1 filter
BlendTorch: A Real-Time, Adaptive Domain Randomization Library
Christoph Heindl, Lukas Brunner, Sebastian Zambal +1
Solving complex computer vision tasks by deep learning techniques relies on large amounts of (supervised) image data, typically unavailable in industrial environments. The lack of…
End-to-End Defect Detection in Automated Fiber Placement Based on Artificially Generated Data
Sebastian Zambal, Christoph Heindl, Christian Eitzinger +1
Automated fiber placement (AFP) is an advanced manufacturing technology that increases the rate of production of composite materials. At the same time, the need for adaptable and f…
Learning to Predict Robot Keypoints Using Artificially Generated Images
Christoph Heindl, Sebastian Zambal, Josef Scharinger
This work considers robot keypoint estimation on color images as a supervised machine learning task. We propose the use of probabilistically created renderings to overcome the lack…
3D Robot Pose Estimation from 2D Images
Christoph Heindl, Sebastian Zambal, Thomas Ponitz +2
This paper considers the task of locating articulated poses of multiple robots in images. Our approach simultaneously infers the number of robots in a scene, identifies joint locat…