Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

Abstract We introduce the Segment Anything (SA) project: a new task, model, and dataset for
image segmentation. Using our efficient model in a data collection loop, we built the largest …

We present a unified framework for understanding 3D hand and object interactions in raw
image sequences from egocentric RGB cameras. Given a single RGB image, our model …

Egocentric videos offer fine-grained information for high-fidelity modeling of human
behaviors. Hands and interacting objects are one crucial aspect of understanding a viewer's …

Egocentric activity recognition is one of the most challenging tasks in video analysis. It
requires a fine-grained discrimination of small objects and their manipulation. While some …

Wearable cameras allow to collect images and videos of humans interacting with the world.
While human-object interactions have been thoroughly investigated in third person vision …

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 propose an end-to-end trainable deep neural network model for egocentric
activity recognition. Our model is built on the observation that egocentric activities are highly …

Wearable cameras allow to acquire images and videos from the user's perspective. These
data can be processed to understand humans behavior. Despite human behavior analysis …

Affordance grounding aims to locate objects'“action possibilities” regions, an essential step
toward embodied intelligence. Due to the diversity of interactive affordance, ie, the …