Human action recognition from various data modalities: A review
Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …
each action. It has a wide range of applications, and therefore has been attracting increasing …
A survey on video-based human action recognition: recent updates, datasets, challenges, and applications
Abstract Human Action Recognition (HAR) involves human activity monitoring task in
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …
Memvit: Memory-augmented multiscale vision transformer for efficient long-term video recognition
While today's video recognition systems parse snapshots or short clips accurately, they
cannot connect the dots and reason across a longer range of time yet. Most existing video …
cannot connect the dots and reason across a longer range of time yet. Most existing video …
Vision-based human activity recognition: a survey
Human activity recognition (HAR) systems attempt to automatically identify and analyze
human activities using acquired information from various types of sensors. Although several …
human activities using acquired information from various types of sensors. Although several …
Autoad ii: The sequel-who, when, and what in movie audio description
Audio Description (AD) is the task of generating descriptions of visual content, at suitable
time intervals, for the benefit of visually impaired audiences. For movies, this presents …
time intervals, for the benefit of visually impaired audiences. For movies, this presents …
A multimodal approach for human activity recognition based on skeleton and RGB data
Human action recognition plays a fundamental role in the design of smart solution for home
environments, particularly in relation to ambient assisted living applications, where the …
environments, particularly in relation to ambient assisted living applications, where the …
Deep learning for deepfakes creation and detection: A survey
Deep learning has been successfully applied to solve various complex problems ranging
from big data analytics to computer vision and human-level control. Deep learning advances …
from big data analytics to computer vision and human-level control. Deep learning advances …
Slowfast networks for video recognition
We present SlowFast networks for video recognition. Our model involves (i) a Slow pathway,
operating at low frame rate, to capture spatial semantics, and (ii) a Fast pathway, operating …
operating at low frame rate, to capture spatial semantics, and (ii) a Fast pathway, operating …
Self-supervised video representation learning by pace prediction
This paper addresses the problem of self-supervised video representation learning from a
new perspective–by video pace prediction. It stems from the observation that human visual …
new perspective–by video pace prediction. It stems from the observation that human visual …
Word-level deep sign language recognition from video: A new large-scale dataset and methods comparison
Vision-based sign language recognition aims at hel** the hearing-impaired people to
communicate with others. However, most existing sign language datasets are limited to a …
communicate with others. However, most existing sign language datasets are limited to a …