TY - GEN
T1 - Emotions in LatAm
T2 - 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2025
AU - Kumar, Pooja Kishore
AU - De Lima Costa, Willams
AU - Nogueira Ferraz E Oliveira, Renato
AU - Teichrieb, Veronica
AU - Talavera Martinez, Estefania
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025/9/15
Y1 - 2025/9/15
N2 - Vision-based emotion recognition uses images or videos to analyze visual cues, such as facial expressions, to infer emotions. Researchers often explore how humans interpret these cues to develop more robust emotion recognition systems. Studies suggest that, while biological factors play a predominant role in allowing this capability, cultural influences shape and adapt universal emotions. Given the role of culture in this process, a major concern is that existing emotion recognition datasets predominantly feature content from North America and Europe, limiting their global representativeness. To bridge this gap, we introduce the Emotions in LatAm dataset (EiLA), a novel dataset comprising emotion recognition data collected exclusively in Latin America. Our goal is to enable future research on emotion recognition from a Responsible AI perspective. Additionally, we benchmark the performance of state-of-the-art and widely used open-source models on the task of Facial Expression Recognition (FER) using EiLA.
AB - Vision-based emotion recognition uses images or videos to analyze visual cues, such as facial expressions, to infer emotions. Researchers often explore how humans interpret these cues to develop more robust emotion recognition systems. Studies suggest that, while biological factors play a predominant role in allowing this capability, cultural influences shape and adapt universal emotions. Given the role of culture in this process, a major concern is that existing emotion recognition datasets predominantly feature content from North America and Europe, limiting their global representativeness. To bridge this gap, we introduce the Emotions in LatAm dataset (EiLA), a novel dataset comprising emotion recognition data collected exclusively in Latin America. Our goal is to enable future research on emotion recognition from a Responsible AI perspective. Additionally, we benchmark the performance of state-of-the-art and widely used open-source models on the task of Facial Expression Recognition (FER) using EiLA.
KW - 2026 OA procedure
UR - https://www.scopus.com/pages/publications/105017855733
U2 - 10.1109/CVPRW67362.2025.00009
DO - 10.1109/CVPRW67362.2025.00009
M3 - Conference contribution
AN - SCOPUS:105017855733
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 41
EP - 47
BT - Proceedings - 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2025
PB - IEEE
Y2 - 11 June 2025 through 15 June 2025
ER -