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 …
Action recognition based on RGB and skeleton data sets: A survey
Action recognition is a major branch of computer vision research. As a widely used
technology, action recognition has been applied to human–computer interaction, intelligent …
technology, action recognition has been applied to human–computer interaction, intelligent …
Toward human activity recognition: a survey
Human activity recognition (HAR) is a complex and multifaceted problem. The research
community has reported numerous approaches to perform HAR. Along with HAR …
community has reported numerous approaches to perform HAR. Along with HAR …
Overview of behavior recognition based on deep learning
K Hu, J Jin, F Zheng, L Weng, Y Ding - Artificial intelligence review, 2023 - Springer
Human behavior recognition has always been a hot spot for research in computer vision.
With the wide application of behavior recognition in virtual reality and short video in recent …
With the wide application of behavior recognition in virtual reality and short video in recent …
Gsrformer: Grounded situation recognition transformer with alternate semantic attention refinement
Grounded Situation Recognition (GSR) aims to generate structured semantic summaries of
images for" human-like''event understanding. Specifically, GSR task not only detects the …
images for" human-like''event understanding. Specifically, GSR task not only detects the …
AI-driven behavior biometrics framework for robust human activity recognition in surveillance systems
The integration of artificial intelligence (AI) into human activity recognition (HAR) in smart
surveillance systems has the potential to revolutionize behavior monitoring. These systems …
surveillance systems has the potential to revolutionize behavior monitoring. These systems …
Posynda: Multi-hypothesis pose synthesis domain adaptation for robust 3d human pose estimation
The current 3D human pose estimators face challenges in adapting to new datasets due to
the scarcity of 2D-3D pose pairs in target domain training sets. We present the Multi …
the scarcity of 2D-3D pose pairs in target domain training sets. We present the Multi …
Vit-ret: Vision and recurrent transformer neural networks for human activity recognition in videos
Human activity recognition is an emerging and important area in computer vision which
seeks to determine the activity an individual or group of individuals are performing. The …
seeks to determine the activity an individual or group of individuals are performing. The …
A fusion of a deep neural network and a hidden Markov model to recognize the multiclass abnormal behavior of elderly people
L Wang, Y Zhou, R Li, L Ding - Knowledge-Based Systems, 2022 - Elsevier
With a rapidly aging population, the health problems of older individuals have attracted
increasing attention. Elderly people are exposed to more health risks, and their behavior can …
increasing attention. Elderly people are exposed to more health risks, and their behavior can …
[HTML][HTML] Low-light aware framework for human activity recognition via optimized dual stream parallel network
Abstract Human Activity Recognition (HAR) plays a crucial role in communication and the
Internet of Things (IoT), by enabling vision sensors to understand and respond to human …
Internet of Things (IoT), by enabling vision sensors to understand and respond to human …