Spatio-temporal attention-based LSTM networks for 3D action recognition and detection
Human action analytics has attracted a lot of attention for decades in computer vision. It is
important to extract discriminative spatio-temporal features to model the spatial and temporal …
important to extract discriminative spatio-temporal features to model the spatial and temporal …
A benchmark dataset and comparison study for multi-modal human action analytics
Large-scale benchmarks provide a solid foundation for the development of action analytics.
Most of the previous activity benchmarks focus on analyzing actions in RGB videos. There is …
Most of the previous activity benchmarks focus on analyzing actions in RGB videos. There is …
Simple to complex transfer learning for action recognition
Recognizing complex human actions is very challenging, since training a robust learning
model requires a large amount of labeled data, which is difficult to acquire. Considering that …
model requires a large amount of labeled data, which is difficult to acquire. Considering that …
Deep appearance and motion learning for egocentric activity recognition
Egocentric activity recognition has recently generated great popularity in computer vision
due to its widespread applications in egocentric video analysis. However, it poses new …
due to its widespread applications in egocentric video analysis. However, it poses new …
Order-aware convolutional pooling for video based action recognition
Most video based action recognition approaches create the video-level representation by
temporally pooling the features extracted at every frame. The pooling methods they adopt …
temporally pooling the features extracted at every frame. The pooling methods they adopt …
Jointly optimization for activity recognition in secure IoT-enabled elderly care applications
M Tao, X Li, W Wei, H Yuan - Applied Soft Computing, 2021 - Elsevier
Elderly care is a significant livelihood project in the increasingly serious aging society.
Nowadays, the wider application of the Internet of Things (IoT) technology on assistant …
Nowadays, the wider application of the Internet of Things (IoT) technology on assistant …
Action recognition using form and motion modalities
Action recognition has attracted increasing interest in computer vision due to its potential
applications in many vision systems. One of the main challenges in action recognition is to …
applications in many vision systems. One of the main challenges in action recognition is to …
Group sparse-based mid-level representation for action recognition
Mid-level parts are shown to be effective for human action recognition in videos. Typically,
these semantic parts are first mined with some heuristic rules, then videos are represented …
these semantic parts are first mined with some heuristic rules, then videos are represented …
Exploring privileged information from simple actions for complex action recognition
Complex action recognition is an important yet challenging problem in computer vision.
Sufficient labeled training data are required for learning a robust model. However, labeling …
Sufficient labeled training data are required for learning a robust model. However, labeling …
Multi-stream deep networks for human action classification with sequential tensor decomposition
H Guo, X Wu, W Feng - Signal Processing, 2017 - Elsevier
Effective spatial-temporal representation of motion information is crucial to human action
classification. In spite of the attempt of most existing methods capturing spatial-temporal …
classification. In spite of the attempt of most existing methods capturing spatial-temporal …