Video-based human action recognition is one of the most important and challenging areas
of research in the field of computer vision. Human action recognition has found many …

Human action recognition and posture prediction aim to recognize and predict respectively
the action and postures of persons in videos. They are both active research topics in …

This work focuses on the task of elderly activity recognition, which is a challenging task due
to the existence of individual actions and human-object interactions in elderly activities …

In practical applications, multi-view data depicting objects from assorted perspectives can
facilitate the accuracy increase of learning algorithms. However, given multi-view data, there …

Skeleton-based gesture recognition methods have achieved high success using Graph
Convolutional Network (GCN), which commonly uses an adjacency matrix to model the …

Deep multi-view representation learning focuses on training a unified low-dimensional
representation for data with multiple sources or modalities. With the rapidly growing attention …

Human action recognition has been applied in many fields, such as video surveillance and
human computer interaction, where it helps to improve performance. Numerous reviews of …

Skeleton representation has attracted a great deal of attention recently as an extremely
robust feature for human action recognition. However, its non-Euclidean structural …

We focus on unsupervised representation learning for skeleton based action recognition.
Existing unsupervised approaches usually learn action representations by motion prediction …

Recently, part-based deep models have achieved promising performance in person re-
identification (Re-ID), yet these models ignore the inter-local relationship of the …