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 review on the long short-term memory model
Long short-term memory (LSTM) has transformed both machine learning and
neurocomputing fields. According to several online sources, this model has improved …
neurocomputing fields. According to several online sources, this model has improved …
A comprehensive study of deep video action recognition
Video action recognition is one of the representative tasks for video understanding. Over the
last decade, we have witnessed great advancements in video action recognition thanks to …
last decade, we have witnessed great advancements in video action recognition thanks to …
System-status-aware adaptive network for online streaming video understanding
Recent years have witnessed great progress in deep neural networks for real-time
applications. However, most existing works do not explicitly consider the general case …
applications. However, most existing works do not explicitly consider the general case …
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 …
Empowering relational network by self-attention augmented conditional random fields for group activity recognition
This paper presents a novel relational network for group activity recognition. The core of our
network is to augment the conditional random fields (CRF), amenable to learning inter …
network is to augment the conditional random fields (CRF), amenable to learning inter …
Human activity recognition (har) using deep learning: Review, methodologies, progress and future research directions
P Kumar, S Chauhan, LK Awasthi - Archives of Computational Methods in …, 2024 - Springer
Human activity recognition is essential in many domains, including the medical and smart
home sectors. Using deep learning, we conduct a comprehensive survey of current state …
home sectors. Using deep learning, we conduct a comprehensive survey of current state …
Videoxum: Cross-modal visual and textural summarization of videos
Video summarization aims to distill the most important information from a source video into
either an abridged video clip or a textual narrative. Existing methods often treat the …
either an abridged video clip or a textual narrative. Existing methods often treat the …
A novel multiple-view adversarial learning network for unsupervised domain adaptation action recognition
domain adaptation action recognition is a hot research topic in machine learning and some
effective approaches have been proposed. However, samples in the target domain with …
effective approaches have been proposed. However, samples in the target domain with …
Dynamic video mix-up for cross-domain action recognition
In recent years, action recognition has been extensively studied. For some general action
datasets, such as UCF101 [1], the recognition accuracy in a specific domain can reach 95 …
datasets, such as UCF101 [1], the recognition accuracy in a specific domain can reach 95 …