5 citations · 7 across the 5 of their papers we have counts for
7 papers
Latent Plans for Task-Agnostic Offline Reinforcement Learning
Erick Rosete-Beas, Oier Mees, Gabriel Kalweit +2
Everyday tasks of long-horizon and comprising a sequence of multiple implicit subtasks still impose a major challenge in offline robot control. While a number of prior methods aime…
Affordance Learning from Play for Sample-Efficient Policy Learning
Jessica Borja-Diaz, Oier Mees, Gabriel Kalweit +3
Robots operating in human-centered environments should have the ability to understand how objects function: what can be done with each object, where this interaction may occur, and…
Composing Pick-and-Place Tasks By Grounding Language
Oier Mees, Wolfram Burgard
Controlling robots to perform tasks via natural language is one of the most challenging topics in human-robot interaction. In this work, we present a robot system that follows unco…
Hindsight for Foresight: Unsupervised Structured Dynamics Models from Physical Interaction
Iman Nematollahi, Oier Mees, Lukas Hermann +1
A key challenge for an agent learning to interact with the world is to reason about physical properties of objects and to foresee their dynamics under the effect of applied forces.…
Learning Object Placements For Relational Instructions by Hallucinating Scene Representations
Oier Mees, Alp Emek, Johan Vertens +1
Robots coexisting with humans in their environment and performing services for them need the ability to interact with them. One particular requirement for such robots is that they…
Self-supervised 3D Shape and Viewpoint Estimation from Single Images for Robotics
Oier Mees, Maxim Tatarchenko, Thomas Brox +1
We present a convolutional neural network for joint 3D shape prediction and viewpoint estimation from a single input image. During training, our network gets the learning signal fr…