Items where Author is "Li, Wenbin"

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Number of items: 9.

Conference or Workshop Item (A Paper)

Wagner, Misha and Basevi, Hector and Shetty, Rakshith and Li, Wenbin and Malinowski, Mateusz and Fritz, Mario and Leonardis, Ales
(2018) Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions.
In: Visual Learning and Embodied Agents in Simulation Environments Workshop at European Conference on Computer Vision.
Conference: ECCV European Conference on Computer Vision

Li, Wenbin and Leonardis, Ales and Fritz, Mario
(2017) Visual stability prediction for robotic manipulation.
In: 2017 IEEE International Conference on Robotics and Automation, ICRA 2017, Singapore, Singapore, May 29 - June 3, 2017.

Li, Wenbin and Fritz, Mario
(2016) Recognition of Ongoing Complex Activities by Sequence Prediction over a Hierarchical Label Space.
In: IEEE Winter Conference on Applications of Computer Vision (WACV).
Conference: WACV IEEE Workshop on Applications of Computer Vision

Li, Wenbin and Fritz, Mario
(2015) Teaching robots the use of human tools from demonstration with non-dexterous end-effectors.
In: 15th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2015, Seoul, South Korea, November 3-5, 2015.

Li, Wenbin and Fritz, Mario
(2012) Recognizing Materials from Virtual Examples.
In: Computer Vision - ECCV 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part IV.
Conference: ECCV European Conference on Computer Vision

Article

Li, Wenbin and Bohg, Jeannette and Fritz, Mario
(2017) Acquiring Target Stacking Skills by Goal-Parameterized Deep Reinforcement Learning.
CoRR, abs/17.

Li, Wenbin and Azimi, Seyedmajid and Leonardis, Ales and Fritz, Mario
(2016) To Fall Or Not To Fall: A Visual Approach to Physical Stability Prediction.
CoRR, abs/16.

Li, Wenbin and Leonardis, Ales and Fritz, Mario
(2016) Visual Stability Prediction and Its Application to Manipulation.
CoRR, abs/16.

Li, Wenbin and Fritz, Mario
(2014) Learning Multi-Scale Representations for Material Classification.
CoRR, abs/14.

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