11 citations · 29 across the 10 of their papers we have counts for
10 papers
Multi Sentence Description of Complex Manipulation Action Videos
Fatemeh Ziaeetabar, Reza Safabakhsh, Saeedeh Momtazi +2
Automatic video description requires the generation of natural language statements about the actions, events, and objects in the video. An important human trait, when we describe a…
A Hierarchical Graph-based Approach for Recognition and Description Generation of Bimanual Actions in Videos
Fatemeh Ziaeetabar, Reza Safabakhsh, Saeedeh Momtazi +2
Nuanced understanding and the generation of detailed descriptive content for (bimanual) manipulation actions in videos is important for disciplines such as robotics, human-computer…
Simulated Mental Imagery for Robotic Task Planning
Shijia Li, Tomas Kulvicius, Minija Tamosiunaite +1
Traditional AI-planning methods for task planning in robotics require a symbolically encoded domain description. While powerful in well-defined scenarios, as well as human-interpre…
Combining Optimal Path Search With Task-Dependent Learning in a Neural Network
Tomas Kulvicius, Minija Tamosiunaite, Florentin Wörgötter
Finding optimal paths in connected graphs requires determining the smallest total cost for traveling along the graph's edges. This problem can be solved by several classical algori…
Bootstrapping Concept Formation in Small Neural Networks
Minija Tamosiunaite, Tomas Kulvicius, Florentin Wörgötter
The question how neural systems (of humans) can perform reasoning is still far from being solved. We posit that the process of forming Concepts is a fundamental step required for t…
Human and Machine Action Prediction Independent of Object Information
Fatemeh Ziaeetabar, Jennifer Pomp, Stefan Pfeiffer +4
Predicting other people's action is key to successful social interactions, enabling us to adjust our own behavior to the consequence of the others' future actions. Studies on actio…
Semantic Image Search for Robotic Applications
Tomas Kulvicius, Irene Markelic, Minija Tamosiunaite +1
Generalization in robotics is one of the most important problems. New generalization approaches use internet databases in order to solve new tasks. Modern search engines can return…
One-shot path planning for multi-agent systems using fully convolutional neural network
Tomas Kulvicius, Sebastian Herzog, Timo Lüddecke +2
Path planning plays a crucial role in robot action execution, since a path or a motion trajectory for a particular action has to be defined first before the action can be executed.…
Generation of Paths in a Maze using a Deep Network without Learning
Tomas Kulvicius, Sebastian Herzog, Minija Tamosiunaite +1
Trajectory- or path-planning is a fundamental issue in a wide variety of applications. Here we show that it is possible to solve path planning for multiple start- and end-points hi…
Action Prediction in Humans and Robots
Florentin Wörgötter, Fatemeh Ziaeetabar, Stefan Pfeiffer +3
Efficient action prediction is of central importance for the fluent workflow between humans and equally so for human-robot interaction. To achieve prediction, actions can be encode…