Researchers have been develo** Hand Gesture Recognition (HGR) systems to enhance
natural, efficient, and authentic human-computer interaction, especially benefiting those who …

Contrastive learning has been successfully leveraged to learn action representations for
addressing the problem of semisupervised skeleton-based action recognition. However …

Gesture recognition has attracted considerable attention owing to its great potential in
applications. Although the great progress has been made recently in multi-modal learning …

Benefited from the powerful ability of spatial temporal Graph Convolutional Networks (ST-
GCNs), skeleton-based human action recognition has gained promising success. However …

Hand gesture recognition from images is a longstanding computer vision task that can be
used to build a potential bridge for human-computer interaction and sign language …

Recently, transform-based tensor nuclear norm (TNN) minimization methods have received
increasing attention for recovering third-order tensors in multi-dimensional imaging …

Facial Action Unit (AU) detection is a crucial task in affective computing and social robotics
as it helps to identify emotions expressed through facial expressions. Anatomically, there are …

In this work, we focus on studying the differentiable relaxations of several linear regression
problems, where the original formulations are usually both nonsmooth with one nonconvex …

Psychological studies have shown that Micro Gestures (MG) are closely linked to human
emotions. MG-based emotion understanding has attracted much attention because it allows …

Current continuous sign language recognition systems generally target on a single
language. When it comes to the multilingual problem, existing solutions often build separate …