Visual7W: Grounded Question Answering in Images. - Yuke Zhu; Oliver Groth; Michael S. Bernstein; Li Fei-Fei 001 (CVPR, 2016)

Analyzing modular CNN architectures for joint depth prediction and semantic segmentation. - Omid Hosseini Jafari; Oliver Groth; Alexander Kirillov; Michael Ying Yang; Carsten Rother (ICRA, 2017)

Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations. - Ranjay Krishna; Yuke Zhu; Oliver Groth; Justin Johnson 001; Kenji Hata; Joshua Kravitz; Stephanie Chen; Yannis Kalantidis; Li-Jia Li 001; David A. Shamma; Michael S. Bernstein; Li Fei-Fei 001 (Int. J. Comput. Vis., 2017)

ShapeStacks: Learning Vision-Based Physical Intuition for Generalised Object Stacking. - Oliver Groth; Fabian B. Fuchs; Ingmar Posner; Andrea Vedaldi (ECCV (1), 2018)

Neural Stethoscopes: Unifying Analytic, Auxiliary and Adversarial Network Probing. - Fabian B. Fuchs; Oliver Groth; Adam R. Kosiorek; Alex Bewley; Markus Wulfmeier; Andrea Vedaldi; Ingmar Posner (CoRR, 2018)

Scrutinizing and De-Biasing Intuitive Physics with Neural Stethoscopes. - Fabian B. Fuchs; Oliver Groth; Adam R. Kosiorek; Alex Bewley; Markus Wulfmeier; Andrea Vedaldi; Ingmar Posner (BMVC, 2019)

Imagine That! Leveraging Emergent Affordances for Tool Synthesis in Reaching Tasks. - Yizhe Wu; Sudhanshu Kasewa; Oliver Groth; Sasha Salter; Li Sun 005; Oiwi Parker Jones; Ingmar Posner (CoRR, 2019)

RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent Spaces. - Sébastien Ehrhardt; Oliver Groth; Áron Monszpart; Martin Engelcke; Ingmar Posner; Niloy J. Mitra; Andrea Vedaldi (NeurIPS, 2020)

Goal-Conditioned End-to-End Visuomotor Control for Versatile Skill Primitives. - Oliver Groth; Chia-Man Hung; Andrea Vedaldi; Ingmar Posner (ICRA, 2021)

Is Curiosity All You Need? On the Utility of Emergent Behaviours from Curious Exploration. - Oliver Groth; Markus Wulfmeier; Giulia Vezzani; Vibhavari Dasagi; Tim Hertweck; Roland Hafner; Nicolas Heess; Martin A. Riedmiller (CoRR, 2021)

RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation. - Konstantinos Bousmalis; Giulia Vezzani; Dushyant Rao; Coline Devin; Alex X. Lee; Maria Bauzá 001; Todor Davchev; Yuxiang Zhou; Agrim Gupta; Akhil Raju; Antoine Laurens; Claudio Fantacci; et al. (CoRR, 2023)

Unlocking the Power of Representations in Long-term Novelty-based Exploration. - Alaa Saade; Steven Kapturowski; Daniele Calandriello; Charles Blundell; Pablo Sprechmann; Leopoldo Sarra; Oliver Groth; Michal Valko; Bilal Piot (ICLR, 2024)

Offline Actor-Critic Reinforcement Learning Scales to Large Models. - Jost Tobias Springenberg; Abbas Abdolmaleki; Jingwei Zhang 001; Oliver Groth; Michael Bloesch; Thomas Lampe; Philemon Brakel; Sarah Bechtle; Steven Kapturowski; Roland Hafner; Nicolas Heess; Martin A. Riedmiller (ICML, 2024)

Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. - Thomas Lampe; Abbas Abdolmaleki; Sarah Bechtle; Sandy H. Huang; Jost Tobias Springenberg; Michael Bloesch; Oliver Groth; Roland Hafner; Tim Hertweck; Michael Neunert; Markus Wulfmeier; Jingwei Zhang 001; et al. (ICRA, 2024)

RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation. - Konstantinos Bousmalis; Giulia Vezzani; Dushyant Rao; Coline Manon Devin; Alex X. Lee; Maria Bauzá Villalonga; Todor Davchev; Yuxiang Zhou; Agrim Gupta; Akhil Raju; Antoine Laurens; Claudio Fantacci; et al. (Trans. Mach. Learn. Res., 2024)

Exploiting Policy Idling for Dexterous Manipulation. - Annie S. Chen; Philemon Brakel; Antonia Bronars; Annie Xie; Sandy H. Huang; Oliver Groth; Maria Bauzá 001; Markus Wulfmeier; Nicolas Heess; Dushyant Rao (CoRR, 2025)