A survey of human action recognition and posture prediction
Human action recognition and posture prediction aim to recognize and predict respectively
the action and postures of persons in videos. They are both active research topics in …
the action and postures of persons in videos. They are both active research topics in …
Actionclip: A new paradigm for video action recognition
The canonical approach to video action recognition dictates a neural model to do a classic
and standard 1-of-N majority vote task. They are trained to predict a fixed set of predefined …
and standard 1-of-N majority vote task. They are trained to predict a fixed set of predefined …
A survey on video action recognition in sports: Datasets, methods and applications
To understand human behaviors, action recognition based on videos is a common
approach. Compared with image-based action recognition, videos provide much more …
approach. Compared with image-based action recognition, videos provide much more …
Actionclip: Adapting language-image pretrained models for video action recognition
The canonical approach to video action recognition dictates a neural network model to do a
classic and standard 1-of-N majority vote task. They are trained to predict a fixed set of …
classic and standard 1-of-N majority vote task. They are trained to predict a fixed set of …
Interaction-aware spatio-temporal pyramid attention networks for action classification
Local features at neighboring spatial positions in feature maps have high correlation since
their receptive fields are often overlapped. Self-attention usually uses the weighted sum (or …
their receptive fields are often overlapped. Self-attention usually uses the weighted sum (or …
[HTML][HTML] Advancing human action recognition: A hybrid approach using attention-based LSTM and 3D CNN
In this paper, we propose a novel approach to video action recognition that integrates a
modified and optimized 3D Convolutional Neural Network, a Long Short-Term Memory …
modified and optimized 3D Convolutional Neural Network, a Long Short-Term Memory …
Learning spatiotemporal and motion features in a unified 2d network for action recognition
Recent methods for action recognition always apply 3D Convolutional Neural Networks
(CNNs) to extract spatiotemporal features and introduce optical flows to present motion …
(CNNs) to extract spatiotemporal features and introduce optical flows to present motion …
人体行为识别方法研究综述.
梁绪， 李文新， 张航宁 - Application Research of Computers …, 2022 - search.ebscohost.com
随着计算机视觉不断发展, 人体行为识别在视频监控, 视频检索和人机交互等诸多领域中展现出
其广泛的应用前景和研究价值. 人体行为识别涉及到对图像内容的理解, 由于人体姿势复杂多样 …
其广泛的应用前景和研究价值. 人体行为识别涉及到对图像内容的理解, 由于人体姿势复杂多样 …
Synchrosqueezing-based short-time fractional Fourier transform
Z Zhao, G Li - IEEE Transactions on Signal Processing, 2023 - ieeexplore.ieee.org
A novel synchrosqueezing transform to the time-frequency representation based on short-
time fractional Fourier transform for strong time-varying signals is proposed in this paper. To …
time fractional Fourier transform for strong time-varying signals is proposed in this paper. To …
A knowledge-based hierarchical causal inference network for video action recognition
Currently, existing action recognition methods mainly use a data-driven method to extract
spatio-temporal representations of actions for recognition. However, this method may face …
spatio-temporal representations of actions for recognition. However, this method may face …