Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …

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 …

Generative adversarial networks (GANs) provide a way to learn deep representations
without extensively annotated training data. They achieve this by deriving backpropagation …

Generative adversarial networks (GANs) present a way to learn deep representations
without extensively annotated training data. These networks achieve learning through …

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 …

Facial expression recognition (FER) is a challenging task due to different expressions under
arbitrary poses. Most conventional approaches either perform face frontalization on a non …

What will the future be? We wonder! In this survey, we explore the gap between current
research in egocentric vision and the ever-anticipated future, where wearable computing …

In this paper, we tackle the problem of egocentric action anticipation, ie, predicting what
actions the camera wearer will perform in the near future and which objects they will interact …

Egocentric action anticipation consists in understanding which objects the camera wearer
will interact with in the near future and which actions they will perform. We tackle the …