The DOI matches its Crossref record; 165 of the 165 references it cites were found in a registry or an index.
A survey on video-based Human Action Recognition: recent updates, datasets, challenges, and applications
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Citations
Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421
3D Convolutional Neural Networks for Human Action Recognition
Ji, S., Xu, W., Yang, M., & Yu, K. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.59 · Cited by 6,235
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
Yan, S., Xiong, Y., & Lin, D. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.12328 · Cited by 5,410
Efficient Processing of Deep Neural Networks: A Tutorial and Survey
Sze, V., Chen, Y.-H., Yang, T.-J., & Emer, J. S. (2017) · Proceedings of the IEEE · doi:10.1109/jproc.2017.2761740 · Cited by 4,215
Extreme learning machine: a new learning scheme of feedforward neural networks
Huang, G.-B., Zhu, Q.-Y., & Siew, C.-K. (2005) · 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541) · doi:10.1109/ijcnn.2004.1380068 · Cited by 4,084
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
Wang, L., Xiong, Y., Wang, Z., Qiao, Y., Lin, D., Tang, X., & Van Gool, L. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46484-8_2 · Cited by 3,958
Real-time human pose recognition in parts from single depth images
Shotton, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M., Moore, R., Kipman, A., & Blake, A. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995316 · Cited by 3,491
Learning realistic human actions from movies
Laptev, I., Marszalek, M., Schmid, C., & Rozenfeld, B. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587756 · Cited by 3,444
Action Recognition with Improved Trajectories
Wang, H., & Schmid, C. (2013) · 2013 IEEE International Conference on Computer Vision · doi:10.1109/iccv.2013.441 · Cited by 3,407
Cited by
Toward Long Video Understanding via Fine-Detailed Video Story Generation
You, Z., Wen, Z., Chen, Y., Li, X., Zeng, R., Wang, Y., & Tan, M. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3514820 · Cited by 11
Deep Learning for Skeleton-Based Human Activity Segmentation: An Autoencoder Approach
Hossen, M. A., Naim, A. G., & Abas, P. E. (2024) · Technologies · doi:10.3390/technologies12070096 · Cited by 7
Metadata
- Authors
- Pareek, P., & Thakkar, A.
- Venue
- Artificial Intelligence Review
- Published
- 2020-09-25
- Volume
- 54
- Issue
- 3
- Pages
- 2259-2322
- ISSN
- 0269-2821 (ISSN-L)
- 1573-7462
- OpenAlex
- W3088102655
- Cited by
- 455
- References
- 165
- FWCI
- 18.40
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A survey on video-based Human Action Recognition: recent updates, datasets, challenges, and applications. https://app.cochat.ai/papers/10.1007/s10462-020-09904-8
- The paper
- Pareek, P., & Thakkar, A. (2021). A survey on video-based Human Action Recognition: recent updates, datasets, challenges, and applications. Artificial Intelligence Review. https://doi.org/10.1007/s10462-020-09904-8
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
