Considering most deep learning-based methods heavily depend on huge labels, it is still a
challenging issue for facial expression recognition to extract discriminative features of …

Video anomaly detection (VAD)–commonly formulated as a multiple-instance learning
problem in a weakly-supervised manner due to its labor-intensive nature–is a challenging …

In this paper, we propose a new, simple, and effective Self-supervised Spatio-temporal
Transformers (SPARTAN) approach to Group Activity Recognition (GAR) using unlabeled …

Micro-expression recognition is one of the most challenging topics in affective computing. It
aims to recognize tiny facial movements difficult for humans to perceive in a brief period, ie …

With the advancement of artificial intelligence (AI) technology, group-level emotion
recognition (GER) has emerged as an important area in analyzing human behavior. Early …

Visual interactivity understanding within visual scenes presents a significant challenge in
computer vision. Existing methods focus on complex interactivities while leveraging a simple …

Video scene graph generation (VidSGG) has emerged as a transformative approach to
capturing and interpreting the intricate relationships among objects and their temporal …

Group emotion recognition (GER) from image has attracted much attention in recent years.
Networks using attention mechanism for GER have shown great potential. However, the …

Social robotics is an emerging area that is becoming present in social spaces, by
introducing autonomous social robots. Social robots offer services, perform tasks, and …

This paper proposes a database for group level emotion recognition in videos. The
motivation is coming from the large number of information which the users are sharing …