A survey on deep learning for human activity recognition
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 …
home. In this study, we provide a comprehensive survey on recent advances and challenges …
A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions
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 …
the computer vision. It has critical application in wide variety of tasks including gaming …
Socratic models: Composing zero-shot multimodal reasoning with language
Large pretrained (eg," foundation") models exhibit distinct capabilities depending on the
domain of data they are trained on. While these domains are generic, they may only barely …
domain of data they are trained on. While these domains are generic, they may only barely …
Ego4d: Around the world in 3,000 hours of egocentric video
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 …
offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household …
Learning video representations from large language models
We introduce LAVILA, a new approach to learning video-language representations by
leveraging Large Language Models (LLMs). We repurpose pre-trained LLMs to be …
leveraging Large Language Models (LLMs). We repurpose pre-trained LLMs to be …
Affordances from human videos as a versatile representation for robotics
Building a robot that can understand and learn to interact by watching humans has inspired
several vision problems. However, despite some successful results on static datasets, it …
several vision problems. However, despite some successful results on static datasets, it …
Ego-exo4d: Understanding skilled human activity from first-and third-person perspectives
Abstract We present Ego-Exo4D a diverse large-scale multimodal multiview video dataset
and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric …
and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric …
Anticipative video transformer
Abstract We propose Anticipative Video Transformer (AVT), an end-to-end attention-based
video modeling architecture that attends to the previously observed video in order to …
video modeling architecture that attends to the previously observed video in order to …
Review of eye tracking metrics involved in emotional and cognitive processes
V Skaramagkas, G Giannakakis… - IEEE Reviews in …, 2021 - ieeexplore.ieee.org
Eye behaviour provides valuable information revealing one's higher cognitive functions and
state of affect. Although eye tracking is gaining ground in the research community, it is not …
state of affect. Although eye tracking is gaining ground in the research community, it is not …
Smart frame selection for action recognition
Video classification is computationally expensive. In this paper, we address theproblem of
frame selection to reduce the computational cost of video classification. Recent work has …
frame selection to reduce the computational cost of video classification. Recent work has …