Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …

We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It
offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household …

Video-based recognition of activities of daily living (ADLs) is being used in ambient assisted
living systems in order to support the independent living of older people. However, current …

Being able to map the activities of others into one's own point of view is one fundamental
human skill even from a very early age. Taking a step toward understanding this human …

We present a comprehensive framework for egocentric interaction recognition using
markerless 3D annotations of two hands manipulating objects. To this end, we propose a …

In this work, we study various existing benchmarks for deepfake detection researches. In
particular, we examine a novel two-stage face swap** algorithm, called FaceShifter, for …

We address the task of jointly determining what a person is doing and where they are
looking based on the analysis of video captured by a headworn camera. We propose a …

This paper explores gaze prediction in dynamic $360^ circ $ immersive videos, emph {ie},
based on the history scan path and VR contents, we predict where a viewer will look at an …

Activity detection and classification are very important for autonomous monitoring of humans
for applications, including assistive living, rehabilitation, and surveillance. Wearable sensors …