A comprehensive survey of vision-based human action recognition methods
Although widely used in many applications, accurate and efficient human action recognition
remains a challenging area of research in the field of computer vision. Most recent surveys …
remains a challenging area of research in the field of computer vision. Most recent surveys …
An empirical review of deep learning frameworks for change detection: Model design, experimental frameworks, challenges and research needs
M Mandal, SK Vipparthi - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
Visual change detection, aiming at segmentation of video frames into foreground and
background regions, is one of the elementary tasks in computer vision and video analytics …
background regions, is one of the elementary tasks in computer vision and video analytics …
Mm-vit: Multi-modal video transformer for compressed video action recognition
J Chen, CM Ho - Proceedings of the IEEE/CVF winter …, 2022 - openaccess.thecvf.com
This paper presents a pure transformer-based approach, dubbed the Multi-Modal Video
Transformer (MM-ViT), for video action recognition. Different from other schemes which …
Transformer (MM-ViT), for video action recognition. Different from other schemes which …
Mamba-nd: Selective state space modeling for multi-dimensional data
In recent years, Transformers have become the de-facto architecture for sequence modeling
on text and a variety of multi-dimensional data, such as images and video. However, the use …
on text and a variety of multi-dimensional data, such as images and video. However, the use …
A CSI-based human activity recognition using deep learning
The Internet of Things (IoT) has become quite popular due to advancements in Information
and Communications technologies and has revolutionized the entire research area in …
and Communications technologies and has revolutionized the entire research area in …
Dmc-net: Generating discriminative motion cues for fast compressed video action recognition
Motion has shown to be useful for video understanding, where motion is typically
represented by optical flow. However, computing flow from video frames is very …
represented by optical flow. However, computing flow from video frames is very …
Depth sensors-based action recognition using a modified K-ary entropy classifier
Surveillance system is acquiring an ample interest in the field of computer vision. Existing
surveillance system usually relies on optical or wearable sensors for indoor and outdoor …
surveillance system usually relies on optical or wearable sensors for indoor and outdoor …
Self-supervised video representation learning by context and motion decoupling
A key challenge in self-supervised video representation learning is how to effectively
capture motion information besides context bias. While most existing works implicitly …
capture motion information besides context bias. While most existing works implicitly …
Multi-attention network for compressed video referring object segmentation
Referring video object segmentation aims to segment the object referred by a given
language expression. Existing works typically require compressed video bitstream to be …
language expression. Existing works typically require compressed video bitstream to be …