The Treachery of Images: Bayesian Scene Keypoints for Deep Policy Learning in Robotic Manipulation

Author:

von Hartz Jan Ole1ORCID,Chisari Eugenio1ORCID,Welschehold Tim1ORCID,Burgard Wolfram2ORCID,Boedecker Joschka1ORCID,Valada Abhinav1ORCID

Affiliation:

1. Department of Computer Science, University of Freiburg, Freiburg, Germany

2. Department of Engineering, University of Technology Nuremberg, Bavaria, Germany

Funder

Albert-Ludwigs-Universität Freiburg

Carl Zeiss Foundation with the ReScaLe project

NVIDIA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Reference39 articles.

1. beta-VAE: Learning basic visual concepts with a constrained variational framework;higgins;Proc Int Conf Learn Representations,0

2. A density-based algorithm for discovering clusters in large spatial databases with noise;ester;Proc Int Conf Knowl Disc Data Mining,0

3. RLBench: The Robot Learning Benchmark & Learning Environment

4. Visual tracking decomposition

5. ImageNet: A large-scale hierarchical image database

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