The DOI matches its Crossref record; 47 of the 50 references it cites were found in a registry or an index.
Connectionist Temporal Modeling for Weakly Supervised Action Labeling
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“recurrent models [27, 9], which can capture latent temporal patterns but are difficult to interpret”
From Temporal Convolutional Networks for Action Segmentation and Detection (2017) · cites this paper as [9]
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Large-Scale Video Classification with Convolutional Neural Networks
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Self-citationFramewise phoneme classification with bidirectional LSTM and other neural network architectures
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Research works printed but not linked: 3
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Cited by
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Temporal Convolutional Networks for Action Segmentation and Detection
Lea, C., Flynn, M. D., Vidal, R., Reiter, A., & Hager, G. D. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.113 · Cited by 2,238
“In the literature, our task goes by the name action segmentation [7, 8, 6, 15, 29, 16, 10] or action detection [28, 20, 21, 25].”
BackgroundMethodNeural Sign Language Translation
Camgöz, N. C., Hadfield, S., Koller, O., Ney, H., & Bowden, R. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00812 · Cited by 871
Human Action Recognition and Prediction: A Survey
Kong, Y., & Fu, Y. (2022) · International Journal of Computer Vision · doi:10.1007/s11263-022-01594-9 · Cited by 890
Singh, K. K., & Lee, Y. J. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.381 · Cited by 724
MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation
Farha, Y. A., & Gall, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00369 · Cited by 673
“There is a huge line of research that addresses the action segmentation task in a weakly supervised setup [2, 10, 14, 21, 5].”
Background
Metadata
- Authors
- Huang, D.-A., Fei-Fei, L., & Niebles, J. C.
- Affiliations
- Stanford University (US)
- Corresponding author
- Huang, De-An
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2016
- Pages
- 137-153
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2477205648
- Cited by
- 226
- References
- 50
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 15 · 2023: 22 · 2022: 32 · 2021: 38 · 2020: 33 · 2019: 28 · 2018: 26 · 2017: 16 · 2016: 3
- FWCI
- 8.45
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Human Pose and Action Recognition
- Physical Sciences › Computer Science › Human-Computer Interaction › Hand Gesture Recognition Systems
- Physical Sciences › Computer Science › Artificial Intelligence › Domain Adaptation and Few-Shot Learning
- Keywords
- video action recognition, connectionist temporal classification, dynamic programming, semi-supervised learning, temporal alignment
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