The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining
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Cites
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.819861 · Cited by 57,892
Squeeze-and-Excitation Networks
Hu, J., Shen, L., & Sun, G. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00745 · Cited by 35,667
Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
Cho, K., van Merrienboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., & Bengio, Y. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1179 · Cited by 25,545
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Ioffe, S. (2024) · arXiv (Cornell University) · doi:10.57702/o9raffed · Cited by 14,214
Multi-scale context aggregation by dilated convolutions
Yu, F., & Koltun, V. (2015) · arXiv · doi:10.48550/arxiv.1511.07122 · Cited by 7,738
Speaker Verification Using Adapted Gaussian Mixture Models
Reynolds, D. A., Quatieri, T. F., & Dunn, R. B. (2000) · Digital Signal Processing · doi:10.1006/dspr.1999.0361 · Cited by 4,268
Robust Recovery of Subspace Structures by Low-Rank Representation
Liu, G., Lin, Z., Yan, S., Sun, J., Yu, Y., & Ma, Y. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2012.88 · Cited by 3,594
Self-citationScope of validity of PSNR in image/video quality assessment
Huynh-Thu, Q., & Ghanbari, M. (2008) · Electronics Letters · doi:10.1049/el:20080522 · Cited by 2,959
Recurrent Neural Network Regularization
Zaremba, W., Sutskever, I., & Vinyals, O. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1409.2329 · Cited by 2,123
Online dictionary learning for sparse coding
Mairal, J., Bach, F., Ponce, J., & Sapiro, G. (2009) · Proceedings of the 26th Annual International Conference on Machine Learning · doi:10.1145/1553374.1553463 · Cited by 2,114
Cited by
(2020) · doi:10.1007/978-3-030-58536-5_24 · Cited by 2,824
Pre-Trained Image Processing Transformer
Chen, H., Wang, Y., Guo, T., Xu, C., Deng, Y., Liu, Z., Ma, S., Xu, C., Xu, C., & Gao, W. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.01212 · Cited by 2,308
Uformer: A General U-Shaped Transformer for Image Restoration
Wang, Z., Cun, X., Bao, J., Zhou, W., Liu, J., & Li, H. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.01716 · Cited by 2,274
Multi-Stage Progressive Image Restoration
Zamir, S. W., Arora, A., Khan, S., Hayat, M., Khan, F. S., Yang, M.-H., & Shao, L. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.01458 · Cited by 2,095
MAXIM: Multi-Axis MLP for Image Processing
Tu, Z., Talebi, H., Zhang, H., Yang, F., Milanfar, P., Bovik, A., & Li, Y. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.00568 · Cited by 616
Metadata
- Authors
- Li, X., Wu, J., Lin, Z., Liu, H., & Zha, H.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 262-277
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2884068670
- Cited by
- 927
- References
- 34
- FWCI
- 21.92
- Type
- conference paper
- Language
- en
- Open access
- green
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- Li, X., Wu, J., Lin, Z., Liu, H., & Zha, H. (2018). Recurrent Squeeze-and-Excitation Context Aggregation Net for Single Image Deraining. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-01234-2_16
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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.
