3 papers
cs.HC2024
Mood as a Contextual Cue for Improved Emotion Inference
Soujanya Narayana, Ibrahim Radwan, Ramanathan Subramanian +1
Psychological studies observe that emotions are rarely expressed in isolation and are typically influenced by the surrounding context. While recent studies effectively harness uni-…
cs.CV2023
Efficient Labelling of Affective Video Datasets via Few-Shot & Multi-Task Contrastive Learning
Ravikiran Parameshwara, Ibrahim Radwan, Akshay Asthana +3
Whilst deep learning techniques have achieved excellent emotion prediction, they still require large amounts of labelled training data, which are (a) onerous and tedious to compile…
cs.HC2023
A Weakly Supervised Approach to Emotion-change Prediction and Improved Mood Inference
Soujanya Narayana, Ibrahim Radwan, Ravikiran Parameshwara +4
Whilst a majority of affective computing research focuses on inferring emotions, examining mood or understanding the \textit{mood-emotion interplay} has received significantly less…