The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Chained Predictions Using Convolutional Neural Networks
Abstract
In this work, we present an adaptation of the sequence-to-sequence model for structured vision tasks. In this model, the output variables for a given input are predicted sequentially using neural networks. The prediction for each output variable depends not only on the input but also on the previously predicted output variables. The model is applied to spatial localization tasks and uses convolutional neural networks (CNNs) for processing input images and a multi-scale deconvolutional architecture for making spatial predictions at each step. We explore the impact of weight sharing with a recurrent connection matrix between consecutive predictions, and compare it to a formulation where these weights are not tied. Untied weights are particularly suited for problems with a fixed sized structure, where different classes of output are predicted at different steps. We show that chain models achieve top performing results on human pose estimation from images and videos.
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Cites
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Xu, K., Ba, J., Kiros, R., Cho, K., Courville, A., Salakhutdinov, R., Zemel, R., & Bengio, Y. (2015) · arXiv · doi:10.48550/arxiv.1502.03044 · Cited by 8,248
Show and tell: A neural image caption generator
Vinyals, O., Toshev, A., Bengio, S., & Erhan, D. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298935 · Cited by 6,318
Self-citationStacked Hourglass Networks for Human Pose Estimation
Newell, A., Yang, K., & Deng, J. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46484-8_29 · Cited by 5,634
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
Bengio, S., Vinyals, O., Jaitly, N., & Shazeer, N. (2015) · arXiv · doi:10.48550/arxiv.1506.03099 · Cited by 1,621
Self-citationHuman Pose Estimation with Iterative Error Feedback
Carreira, J., Agrawal, P., Fragkiadaki, K., & Malik, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.512 · Cited by 805
Cited by
Deep High-Resolution Representation Learning for Human Pose Estimation
Sun, K., Xiao, B., Liu, D., & Wang, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00584 · Cited by 5,984
Papandreou, G., Zhu, T., Chen, L.-C., Gidaris, S., Tompson, J., & Murphy, K. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01264-9_17 · Cited by 621
Distribution-Aware Coordinate Representation for Human Pose Estimation
Zhang, F., Zhu, X., Dai, H., Ye, M., & Zhu, C. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00712 · Cited by 588
2D/3D Pose Estimation and Action Recognition Using Multitask Deep Learning
Luvizon, D. C., Picard, D., & Tabia, H. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00539 · Cited by 555
Monocular human pose estimation: A survey of deep learning-based methods
Chen, Y., Tian, Y., & He, M. (2020) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2019.102897 · Cited by 441
Metadata
- Authors
- Gkioxari, G., Toshev, A., & Jaitly, N.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2016
- Pages
- 728-743
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2375583958
- Cited by
- 183
- References
- 5
- FWCI
- 11.16
- Type
- conference paper
- Language
- en
- Open access
- closed
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