Progress of human action recognition research in the last ten years: a comprehensive survey
Abstract Human Action Recognition (HAR) has achieved a remarkable milestone in the field
of computer vision. Apart from its varied applications in human–computer interactions …
of computer vision. Apart from its varied applications in human–computer interactions …
Trear: Transformer-based rgb-d egocentric action recognition
In this article, we propose a transformer-based RGB-D egocentric action recognition
framework, called Trear. It consists of two modules: 1) interframe attention encoder and 2) …
framework, called Trear. It consists of two modules: 1) interframe attention encoder and 2) …
Sonar image target detection based on adaptive global feature enhancement network
Z Wang, S Zhang, W Huang, J Guo… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Automatic underwater target detection plays a vital role in sonar image processing and
analysis, and its core task is to discriminate target categories and achieve precise …
analysis, and its core task is to discriminate target categories and achieve precise …
Attend and guide (ag-net): A keypoints-driven attention-based deep network for image recognition
This article presents a novel keypoints-based attention mechanism for visual recognition in
still images. Deep Convolutional Neural Networks (CNNs) for recognizing images with …
still images. Deep Convolutional Neural Networks (CNNs) for recognizing images with …
Adaptive spatiotemporal representation learning for skeleton-based human action recognition
How do humans recognize an action or an interaction in the real world? Due to the diversity
of viewing perspectives, it is a challenge for humans to identify a regular activity when they …
of viewing perspectives, it is a challenge for humans to identify a regular activity when they …
An sAR ship object detection algorithm based on feature information efficient representation network
J Yu, T Wu, S Zhou, H Pan, X Zhang, W Zhang - Remote Sensing, 2022 - mdpi.com
In the synthetic aperture radar (SAR) ship image, the target size is small and dense, the
background is complex and changeable, the ship target is difficult to distinguish from the …
background is complex and changeable, the ship target is difficult to distinguish from the …
An evolving ensemble model of multi-stream convolutional neural networks for human action recognition in still images
Still image human action recognition (HAR) is a challenging problem owing to limited
sources of information and large intra-class and small inter-class variations which requires …
sources of information and large intra-class and small inter-class variations which requires …
Ensembled transfer learning based multichannel attention networks for human activity recognition in still images
Human activity recognition is one of the most difficult tasks in computer vision. Due to the
lack of time information, detecting human activities from still photos is more difficult than …
lack of time information, detecting human activities from still photos is more difficult than …
Ajenet: Adaptive joints enhancement network for abnormal behavior detection in office scenario
With the increasing popularity of intelligent surveillance systems, abnormal behavior
detection of human beings based on computer vision is attracting more attention. It aims to …
detection of human beings based on computer vision is attracting more attention. It aims to …
FastPicker: Adaptive independent two-stage video-to-video summarization for efficient action recognition
Video datasets suffer from huge inter-frame redundancy, which prevents deep networks from
learning effectively and increases computational costs. Therefore, several methods adopt …
learning effectively and increases computational costs. Therefore, several methods adopt …