59 citations · 194 across the 46 of their papers we have counts for
13 papers · 1 filter
Self-supervised reinforcement learning for speaker localisation with the iCub humanoid robot
Jonas Gonzalez-Billandon, Lukas Grasse, Matthew Tata +2
In the future robots will interact more and more with humans and will have to communicate naturally and efficiently. Automatic speech recognition systems (ASR) will play an importa…
Incorporating Rivalry in Reinforcement Learning for a Competitive Game
Pablo Barros, Ana Tanevska, Ozge Yalcin +1
Recent advances in reinforcement learning with social agents have allowed us to achieve human-level performance on some interaction tasks. However, most interactive scenarios do no…
The FaceChannelS: Strike of the Sequences for the AffWild 2 Challenge
Pablo Barros, Alessandra Sciutti
Predicting affective information from human faces became a popular task for most of the machine learning community in the past years. The development of immense and dense deep neur…
The FaceChannel: A Fast & Furious Deep Neural Network for Facial Expression Recognition
Pablo Barros, Nikhil Churamani, Alessandra Sciutti
Current state-of-the-art models for automatic Facial Expression Recognition (FER) are based on very deep neural networks that are effective but rather expensive to train. Given the…
Action similarity judgment based on kinematic primitives
Vipul Nair, Paul Hemeren, Alessia Vignolo +7
Understanding which features humans rely on -- in visually recognizing action similarity is a crucial step towards a clearer picture of human action perception from a learning and…
Moody Learners -- Explaining Competitive Behaviour of Reinforcement Learning Agents
Pablo Barros, Ana Tanevska, Francisco Cruz +1
Designing the decision-making processes of artificial agents that are involved in competitive interactions is a challenging task. In a competitive scenario, the agent does not only…