3D Convolutional Neural Networks for Human Action Recognition

@article{Ji20103DCN,
  title={3D Convolutional Neural Networks for Human Action Recognition},
  author={Shuiwang Ji and Wei Xu and Ming Yang and Kai Yu},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2010},
  volume={35},
  pages={221-231}
}
We consider the automated recognition of human actions in surveillance videos. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. Convolutional neural networks (CNNs) are a type of deep model that can act directly on the raw inputs. However, such models are currently limited to handling 2D inputs. In this paper, we develop a novel 3D CNN model for action recognition. This model extracts features from both the spatial and the temporal… CONTINUE READING
Highly Influential
This paper has highly influenced 103 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 2,291 citations. REVIEW CITATIONS
Related Discussions
This paper has been referenced on Twitter 3 times. VIEW TWEETS

Citations

Publications citing this paper.
Showing 1-10 of 1,266 extracted citations

Action recognition with deep neural networks

2017 25th Signal Processing and Communications Applications Conference (SIU) • 2017
View 11 Excerpts
Highly Influenced

A Deep Structured Model with Radius–Margin Bound for 3D Human Activity Recognition

International Journal of Computer Vision • 2015
View 10 Excerpts
Highly Influenced

Deep Dynamic Neural Networks for Gesture Segmentation and Recognition

ECCV Workshops • 2014
View 10 Excerpts
Method Support
Highly Influenced

2,292 Citations

0200400600'10'13'16'19
Citations per Year
Semantic Scholar estimates that this publication has 2,292 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 57 references

A Biologically Inspired System for Action Recognition

2007 IEEE 11th International Conference on Computer Vision • 2007
View 6 Excerpts
Highly Influenced

Recognizing human actions: a local SVM approach

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. • 2004
View 6 Excerpts
Highly Influenced

Human action detection by boosting efficient motion features

2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops • 2009
View 4 Excerpts
Highly Influenced

Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition

2007 IEEE Conference on Computer Vision and Pattern Recognition • 2007
View 5 Excerpts
Highly Influenced

A Fast Learning Algorithm for Deep Belief Nets

Neural Computation • 2006
View 4 Excerpts
Highly Influenced

Hidden Part Models for Human Action Recognition: Probabilistic versus Max Margin

IEEE Transactions on Pattern Analysis and Machine Intelligence • 2011