Egocentric vision (aka first-person vision–FPV) applications have thrived over the past few
years, thanks to the availability of affordable wearable cameras and large annotated …

We propose to forecast future hand-object interactions given an egocentric video. Instead of
predicting action labels or pixels, we directly predict the hand motion trajectory and the …

Since its introduction in 2018, EPIC-KITCHENS has attracted attention as the largest
egocentric video benchmark, offering a unique viewpoint on people's interaction with …

Online continual learning from data streams in dynamic environments is a critical direction in
the computer vision field. However, realistic benchmarks and fundamental studies in this line …

Surveillance system is acquiring an ample interest in the field of computer vision. Existing
surveillance system usually relies on optical or wearable sensors for indoor and outdoor …

We introduce an approach for pre-training egocentric video models using large-scale third-
person video datasets. Learning from purely egocentric data is limited by low dataset scale …

Recognition of human behavior plays an important role in context-aware applications.
However, it is still a challenge for end-users to build personalized applications that …

The egocentric action recognition EAR field has recently increased its popularity due to the
affordable and lightweight wearable cameras available nowadays such as GoPro and …

Egocentric videos can bring a lot of information about how humans perceive the world and
interact with the environment, which can be beneficial for the analysis of human behaviour …

Video based Human Action Recognition (HAR) is an active research field of Machine
Learning (ML) and human detection in videos is the most important step in action …