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Online Temporal Action Localization with Memory-Augmented Transformer
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“This approach ensures that the most relevant temporal features are preserved, improving the model's ability to localize actions accurately over time.”
From The AI Hippocampus: How Far are We From Human Memory? (2026) · cites this paper as Song et al., 2024
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End-to-End Object Detection with Transformers
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TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals
Gao, J., Yang, Z., Sun, C., Chen, K., & Nevatia, R. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.392 · Cited by 498
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Cited by
Sorted by citations
The AI Hippocampus: How Far are We From Human Memory?
Jia, Z., Li, J., Kang, Y., Wang, Y., Wu, T., Wang, Q., Wang, X., Zhang, S., Shen, J., Li, Q., et al. (2026) · arXiv · doi:10.48550/arxiv.2601.09113
Metadata
- Authors
- Song, Y., Kim, D., Cho, M., & Kwak, S.
- Affiliations
- Pohang University of Science and Technology (KR)
- Corresponding author
- Song, Youngkil
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Nature Switzerland
- Published
- 2024-12-06
- Pages
- 74-91
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W4405078822
- Cited by
- 3
- References
- 2
- Citations by year
- 2026: 3
- FWCI
- 0.62
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Funders
- Ministry of Science and ICT, South Korea (RS-2019II191906, 2021-II212068, 2019-II191906, RS-2021-II212068)
- Institute for Information and Communications Technology Promotion (RS-2022-II220290, 2022-, RS‐2021‐II212068, RS-2019-II191906)
- 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 › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Keywords
- memory-augmented transformer, video streaming, video action recognition
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- Song, Y., Kim, D., Cho, M., & Kwak, S. (2025). Online Temporal Action Localization with Memory-Augmented Transformer. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-031-72655-2_5