Viktor Schmuck

According to our database, Viktor Schmuck authored at least 9 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Self-supervised prediction of the intention to interact with a service robot.

Gabriele Abbate, Alessandro Giusti, Viktor Schmuck, Oya Çeliktutan, Antonio Paolillo

Robotics Auton. Syst., January, 2024

2023

iGROWL: Improved Group Detection With Link Prediction.

Viktor Schmuck, Oya Çeliktutan

IEEE Trans. Biom. Behav. Identity Sci., July, 2023

Gesticulating with NAO: Real-time Context-Aware Co-Speech Gesture Generation for Human-Robot Interaction.

Nguyen Tan Viet Tuyen, Viktor Schmuck, Oya Çeliktutan

Proceedings of the International Conference on Multimodal Interaction, 2023

The KCL-SAIR team's entry to the GENEA Challenge 2023 Exploring Role-based Gesture Generation in Dyadic Interactions: Listener vs. Speaker.

Viktor Schmuck, Nguyen Tan Viet Tuyen, Oya Çeliktutan

Proceedings of the International Conference on Multimodal Interaction, 2023

2021

GROWL: Group Detection With Link Prediction.

Viktor Schmuck, Oya Çeliktutan

Proceedings of the 16th IEEE International Conference on Automatic Face and Gesture Recognition, 2021

2020

Robocentric Conversational Group Discovery.

Viktor Schmuck, Tingran Sheng, Oya Çeliktutan

Proceedings of the 29th IEEE International Conference on Robot and Human Interactive Communication, 2020

2019

Teaching Pepper Robot to Recognize Emotions of Traumatic Brain Injured Patients Using Deep Neural Networks.

Chaudhary Muhammad Aqdus Ilyas, Viktor Schmuck, Muhammad Ahsanul Haque, Kamal Nasrollahi, Matthias Rehm, Thomas B. Moeslund

Proceedings of the 28th IEEE International Conference on Robot and Human Interactive Communication, 2019

OPTISIA: An Evolutionary Approach to Parameter Optimisation in a Family of Point-Set Pattern-Discovery Algorithms.

Viktor Schmuck, David Meredith

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

training networks separately on static and dynamic obstacles improves collision avoidance during indoor robot navigation.

Viktor Schmuck, David Meredith

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019