3 accepted papers
We propose a real-time RGB-based pipeline for object detection and 6D pose estimation. Our novel 3D orientation estimation is based on a variant of the Denoising Autoencoder that is trained on simulated views of a 3D model using Domain Randomization. This so-called Augmented Autoencoder has several…
We present an approach to automatically assign semantic labels to rooms reconstructed from 3D RGB maps of apartments. Evidence for the room types is generated using state-of-the-art deep-learning techniques for scene classification and object detection based on automatically generated virtual RGB vi…
In this paper, we address the problem of learning to classify new object classes and instances by adapting a previously trained classifier. The main challenges here are the small amount of newly available training data and the large change in appearance between the new and the old data. To address t