Abstract Human Action Recognition (HAR) involves human activity monitoring task in
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …

Human activity recognition has been an important area of computer vision research since
the 1980s. Various approaches have been proposed with a great portion of them addressing …

We present AssemblyHands, a large-scale benchmark dataset with accurate 3D hand pose
annotations, to facilitate the study of egocentric activities with challenging hand-object …

Recent years have witnessed rapid progress in detecting and recognizing individual object
instances. To understand the situation in a scene, however, computers need to recognize …

In this work we study the use of 3D hand poses to recognize first-person dynamic hand
actions interacting with 3D objects. Towards this goal, we collected RGB-D video sequences …

In recent years, there has been a proliferation of works on human action classification from
depth sequences. These works generally present methods and/or feature representations …

RNN-based approaches have achieved outstanding performance on action recognition with
skeleton inputs. Currently these methods limit their inputs to coordinates of joints and …

Human action recognition from videos is a challenging machine vision task with multiple
important application domains, such as humanrobot/machine interaction, interactive …

Spatiotemporal human representation based on 3D visual perception data is a rapidly
growing research area. Representations can be broadly categorized into two groups …

Human activity recognition has potential to impact a wide range of applications from
surveillance to human computer interfaces to content based video retrieval. Recently, the …