7 papers
Efficient and Interpretable Body-Based Emotion Recognition with Lightweight Temporal Convolutional Networks
Christian Arzate Cruz, Stefanos Gkikas, Houshyar Asadi
Body-based emotion recognition is important for real-time affective systems, but graph-based skeleton models can be computationally expensive. This paper studies whether lightweigh…
ReFace: Reorganizing Facial Spatiotemporal Representations for Improved Pain Assessment
Stefanos Gkikas, Yu Fang, Christian Arzate Cruz +2
Automatic pain assessment from facial video remains challenging due to the spatial heterogeneity of pain-related facial cues. This study proposes ReFace, a spatial reorganization p…
A Unified Tokenization Framework for Pain Recognition using Heterogeneous 3D Modalities
Stefanos Gkikas, Christian Arzate Cruz, Valentina Becchetti +3
Pain is a complex and pervasive phenomenon affecting a large percentage of the population, and accurate assessment is essential for effective clinical management and intervention.…
One-Block Transformer (1BT) for EEG-Based Cognitive Workload Assessment
Stefanos Gkikas, Christian Arzate Cruz, Thomas Kassiotis +3
Accurate and continuous estimation of cognitive workload is fundamental to creating adaptive human-machine systems. However, designing architectures that balance representational c…
A Lightweight Transformer for Pain Recognition from Brain Activity
Stefanos Gkikas, Christian Arzate Cruz, Yu Fang +6
Pain is a multifaceted and widespread phenomenon with substantial clinical and societal burden, making reliable automated assessment a critical objective. This paper presents a lig…
Efficient Emotion-Aware Iconic Gesture Prediction for Robot Co-Speech
Edwin C. Montiel-Vazquez, Christian Arzate Cruz, Stefanos Gkikas +3
Co-speech gestures increase engagement and improve speech understanding. Most data-driven robot systems generate rhythmic beat-like motion, yet few integrate semantic emphasis. To…