Search Results for author:
Found 10 papers, 2 papers with code
Greek Sign Language Recognition for the SL-ReDu Learning Platform
There has been increasing interest lately in developing education tools for sign language (SL) learning that enable self-assessment and objective evaluation of learners’ SL productions, assisting both students and their instructors.
Multimodal Locally Enhanced Transformer for Continuous Sign Language Recognition
In this paper, we propose a novel Transformer-based approach for continuous sign language recognition (CSLR) from videos, aiming to address the shortcomings of traditional Transformers in learning local semantic context of SL.
Sign Language Recognition via Deformable 3D Convolutions and Modulated Graph Convolutional Networks
Automatic sign language recognition (SLR) remains challenging, especially when employing RGB video alone (i. e., with no depth or special glove-based input) and under a signer-independent (SI) framework, due to inter-personal signing variation.
Ranked #1 on
Sign Language Recognition
on GSL
Accurate and Resource-Efficient Lipreading with Efficientnetv2 and Transformers
We present a novel resource-efficient end-to-end architecture for lipreading that achieves state-of-the-art results on a popular and challenging benchmark.
Ranked #2 on
Lipreading
on Lip Reading in the Wild
Emotion Understanding in Videos Through Body, Context, and Visual-Semantic Embedding Loss
We present our winning submission to the First International Workshop on Bodily Expressed Emotion Understanding (BEEU) challenge.
ChildBot: Multi-Robot Perception and Interaction with Children
In this paper we present an integrated robotic system capable of participating in and performing a wide range of educational and entertainment tasks, in collaboration with one or more children.
A Deep Learning Approach to Object Affordance Segmentation
In particular, we design an autoencoder that is trained using ground-truth labels of only the last frame of the sequence, and is able to infer pixel-wise affordance labels in both videos and static images.
Fusing Body Posture with Facial Expressions for Joint Recognition of Affect in Child-Robot Interaction
In this paper we address the problem of multi-cue affect recognition in challenging scenarios such as child-robot interaction.
Deep Affordance-grounded Sensorimotor Object Recognition
It is well-established by cognitive neuroscience that human perception of objects constitutes a complex process, where object appearance information is combined with evidence about the so-called object "affordances", namely the types of actions that humans typically perform when interacting with them.
A hierarchical approach with feature selection for emotion recognition from speech
We examine speaker independent emotion classification from speech, reporting experiments on the Berlin database across six basic emotions.
