The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
DeepPose: Human Pose Estimation via Deep Neural Networks
Open accessAbstract
We propose a method for human pose estimation based on Deep Neural Networks (DNNs). The pose estimation is formulated as a DNN-based regression problem towards body joints. We present a cascade of such DNN regres- sors which results in high precision pose estimates. The approach has the advantage of reasoning about pose in a holistic fashion and has a simple but yet powerful formula- tion which capitalizes on recent advances in Deep Learn- ing. We present a detailed empirical analysis with state-of- art or better performance on four academic benchmarks of diverse real-world images.
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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
The Representation and Matching of Pictorial Structures
Fischler, M. A., & Elschlager, R. A. (1973) · IEEE Transactions on Computers · doi:10.1109/t-c.1973.223602 · Cited by 1,322
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Cited by
Going deeper with convolutions
Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298594 · Cited by 48,562
Self-citationSqueeze-and-Excitation Networks
Hu, J., Shen, L., & Sun, G. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00745 · Cited by 35,667
Rethinking the Inception Architecture for Computer Vision
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., & Wojna, Z. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.308 · Cited by 32,138
Self-citationSqueeze-and-Excitation Networks
Hu, J., Shen, L., Albanie, S., Sun, G., & Wu, E. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2913372 · Cited by 12,157
Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields
Cao, Z., Simon, T., Wei, S.-E., & Sheikh, Y. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.143 · Cited by 7,539
“To obtain reliable local observations of body parts, Convolu-tional Neural Networks (CNNs) have been widely used, and have significantly boosted the accuracy on body pose estimation [23, 38, 24, 34, 35, 7, 36, 6].”
Method
Metadata
- Authors
- Toshev, A., & Szegedy, C.
- Venue
- 2014 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2014-06
- Pages
- 1653-1660
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2113325037
- Cited by
- 3,185
- References
- 2
- FWCI
- 94.60
- Type
- conference paper
- Language
- en
- Open access
- green
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- Toshev, A., & Szegedy, C. (2014). DeepPose: Human Pose Estimation via Deep Neural Networks. 2014 IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2014.214
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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).
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