Sensor-based and vision-based human activity recognition: A comprehensive survey

LM Dang, K Min, H Wang, MJ Piran, CH Lee, H Moon - Pattern Recognition, 2020 - Elsevier
Human activity recognition (HAR) technology that analyzes data acquired from various types
of sensing devices, including vision sensors and embedded sensors, has motivated the …

A survey of robot learning strategies for human-robot collaboration in industrial settings

D Mukherjee, K Gupta, LH Chang, H Najjaran - Robotics and Computer …, 2022 - Elsevier
Increased global competition has placed a premium on customer satisfaction, and there is a
greater demand for manufacturers to be flexible with their products and services. This …

Vision-based human activity recognition: a survey

DR Beddiar, B Nini, M Sabokrou, A Hadid - Multimedia Tools and …, 2020 - Springer
Human activity recognition (HAR) systems attempt to automatically identify and analyze
human activities using acquired information from various types of sensors. Although several …

Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding

J Liu, A Shahroudy, M Perez, G Wang… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Research on depth-based human activity analysis achieved outstanding performance and
demonstrated the effectiveness of 3D representation for action recognition. The existing …

Multi-scale spatial temporal graph convolutional network for skeleton-based action recognition

Z Chen, S Li, B Yang, Q Li, H Liu - … of the AAAI conference on artificial …, 2021 - ojs.aaai.org
Graph convolutional networks have been widely used for skeleton-based action recognition
due to their excellent modeling ability of non-Euclidean data. As the graph convolution is a …

An attention enhanced graph convolutional lstm network for skeleton-based action recognition

C Si, W Chen, W Wang, L Wang… - Proceedings of the …, 2019 - openaccess.thecvf.com
Skeleton-based action recognition is an important task that requires the adequate
understanding of movement characteristics of a human action from the given skeleton …

Monocular human pose estimation: A survey of deep learning-based methods

Y Chen, Y Tian, M He - Computer vision and image understanding, 2020 - Elsevier
Vision-based monocular human pose estimation, as one of the most fundamental and
challenging problems in computer vision, aims to obtain posture of the human body from …

A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions

SK Yadav, K Tiwari, HM Pandey, SA Akbar - Knowledge-Based Systems, 2021 - Elsevier
Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …

Semantics-guided neural networks for efficient skeleton-based human action recognition

P Zhang, C Lan, W Zeng, J **ng… - proceedings of the …, 2020 - openaccess.thecvf.com
Skeleton-based human action recognition has attracted great interest thanks to the easy
accessibility of the human skeleton data. Recently, there is a trend of using very deep …

Temporal attention unit: Towards efficient spatiotemporal predictive learning

C Tan, Z Gao, L Wu, Y Xu, J **a… - Proceedings of the …, 2023 - openaccess.thecvf.com
Spatiotemporal predictive learning aims to generate future frames by learning from historical
frames. In this paper, we investigate existing methods and present a general framework of …