The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Video Summarization Using Fully Convolutional Sequence Networks
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Cites
Hochreiter, S., & Schmidhuber, J. (1997) · Neural Computation · doi:10.1162/neco.1997.9.8.1735 · Cited by 102,318
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
Fully convolutional networks for semantic segmentation
Long, J., Shelhamer, E., & Darrell, T. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298965 · Cited by 38,834
Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2016) · arXiv · doi:10.48550/arxiv.1606.00915 · Cited by 22,392
Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., & Yuille, A. L. (2018) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2017.2699184 · Cited by 22,392
Advances in neural information processing systems 7
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Bidirectional recurrent neural networks
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Learning Spatiotemporal Features with 3D Convolutional Networks
Tran, D., Bourdev, L., Fergus, R., Torresani, L., & Paluri, M. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.510 · Cited by 9,593
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
Bai, S., Kolter, J. Z., & Koltun, V. (2018) · arXiv · doi:10.48550/arxiv.1803.01271 · Cited by 4,655
2013 IEEE International Conference on Computer Vision
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Research works printed but not linked: 6
- Joshi, N., Kienzle, W., Toelle, M., Uyttendaele, M., Cohen, M.F.: Real-time hyperlapse creation via optimal frame selection. ACM Trans. Graph. 34(4), 63 (2015) · doi:10.1145/2766954
- Kang, H.W., Chen, X.Q.: Space-time video montage. In: IEEE Conference on Computer Vision and Pattern Recognition (2006)
- Li, Y., Merialdo, B.: Multi-video summarization based on video-MMR. In: Workshop on Image Analysis for Multimedia Interactive Services (2010) · doi:10.1109/cbmi.2010.5529899
- Mundur, P., Rao, Y., Yesha, Y.: Keyframe-based video summarization using delaunay clustering. Int. J. Digit. Libr. 6(2), 219–232 (2006) · doi:10.1007/s00799-005-0129-9
- Poleg, Y., Halperin, T., Arora, C., Peleg, S.: EgoSampling: fast-forward and stereo for egocentric videos. In: IEEE Conference on Computer Vision and Pattern Recognition (2015) · doi:10.1109/cvpr.2015.7299109
- Pritch, Y., Rav-Acha, A., Peleg, S.: Nonchronological video synopsis and indexing. IEEE Trans. Pattern Anal. Mach. Intell. 30(11), 1971–1984 (2008) · doi:10.1109/tpami.2008.29
Cited by
Mai, S., Xing, S., & Hu, H. (2021) · IEEE/ACM Transactions on Audio, Speech, and Language Processing · doi:10.1109/taslp.2021.3068598 · Cited by 89
Stacked Memory Network for Video Summarization
Wang, J., Wang, W., Wang, Z., Wang, L., Feng, D., & Tan, T. (2019) · Proceedings of the 27th ACM International Conference on Multimedia · doi:10.1145/3343031.3350992 · Cited by 60
Metadata
- Authors
- Rochan, M., Ye, L., & Wang, Y.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 358-374
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2804194431
- Cited by
- 287
- References
- 38
- FWCI
- 7.62
- Type
- conference paper
- Language
- en
- Open access
- green
- Licence
- www.springer.com/tdm (tdm)
- www.springer.com/tdm (vor)
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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).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.