The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
MAN: Moment Alignment Network for Natural Language Moment Retrieval via Iterative Graph Adjustment
Open accessAbstract
This research strives for natural language moment retrieval in long, untrimmed video streams. The problem is not trivial especially when a video contains multiple moments of interests and the language describes complex temporal dependencies, which often happens in real scenarios. We identify two crucial challenges: semantic misalignment and structural misalignment. However, existing approaches treat different moments separately and do not explicitly model complex moment-wise temporal relations. In this paper, we present Moment Alignment Network (MAN), a novel framework that unifies the candidate moment encoding and temporal structural reasoning in a single-shot feed-forward network. MAN naturally assigns candidate moment representations aligned with language semantics over different temporal locations and scales. Most importantly, we propose to explicitly model moment-wise temporal relations as a structured graph and devise an iterative graph adjustment network to jointly learn the best structure in an end-to-end manner. We evaluate the proposed approach on two challenging public benchmarks DiDeMo and Charades-STA, where our MAN significantly outperforms the state-of-the-art by a large margin.
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Cites
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Self-citationLearning Spatiotemporal Features with 3D Convolutional Networks
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Cited by
Wang, X., Huang, Q., Celikyilmaz, A., Gao, J., Shen, D., Wang, Y.-F., Wang, W. Y., & Zhang, L. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00679 · Cited by 522
Self-citationVaTeX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research
Wang, X., Wu, J., Chen, J., Li, L., Wang, Y.-F., & Wang, W. Y. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00468 · Cited by 486
Self-citationLearning 2D Temporal Adjacent Networks for Moment Localization with Natural Language
Zhang, S., Peng, H., Fu, J., & Luo, J. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i07.6984 · Cited by 482
Local-Global Video-Text Interactions for Temporal Grounding
Mun, J., Cho, M., & Han, B. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.01082 · Cited by 303
Metadata
- Authors
- Zhang, D., Dai, X., Wang, X., Wang, Y.-F., & Davis, L. S.
- Venue
- 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2019-06
- Pages
- 1247-1257
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2962869524
- Cited by
- 331
- References
- 60
- FWCI
- 15.43
- Type
- conference paper
- Language
- en
- Open access
- green
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- Zhang, D., Dai, X., Wang, X., Wang, Y.-F., & Davis, L. S. (2019). MAN: Moment Alignment Network for Natural Language Moment Retrieval via Iterative Graph Adjustment. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/cvpr.2019.00134
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