93 citations · 202 across the 37 of their papers we have counts for
5 papers · 1 filter
Knowing Earlier what Right Means to You: A Comprehensive VQA Dataset for Grounding Relative Directions via Multi-Task Learning
Kyra Ahrens, Matthias Kerzel, Jae Hee Lee +2
Spatial reasoning poses a particular challenge for intelligent agents and is at the same time a prerequisite for their successful interaction and communication in the physical worl…
What is Right for Me is Not Yet Right for You: A Dataset for Grounding Relative Directions via Multi-Task Learning
Jae Hee Lee, Matthias Kerzel, Kyra Ahrens +2
Understanding spatial relations is essential for intelligent agents to act and communicate in the physical world. Relative directions are spatial relations that describe the relati…
Enhancing a Neurocognitive Shared Visuomotor Model for Object Identification, Localization, and Grasping With Learning From Auxiliary Tasks
Matthias Kerzel, Fares Abawi, Manfred Eppe +1
We present a follow-up study on our unified visuomotor neural model for the robotic tasks of identifying, localizing, and grasping a target object in a scene with multiple objects.…
Solving Visual Object Ambiguities when Pointing: An Unsupervised Learning Approach
Doreen Jirak, David Biertimpel, Matthias Kerzel +1
Whenever we are addressing a specific object or refer to a certain spatial location, we are using referential or deictic gestures usually accompanied by some verbal description. Es…
What can computational models learn from human selective attention? A review from an audiovisual crossmodal perspective
Di Fu, Cornelius Weber, Guochun Yang +6
Selective attention plays an essential role in information acquisition and utilization from the environment. In the past 50 years, research on selective attention has been a centra…