{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T11:54:20Z","timestamp":1767873260512,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":33,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819557011","type":"print"},{"value":"9789819557028","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-5702-8_17","type":"book-chapter","created":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T08:29:31Z","timestamp":1767860971000},"page":"240-254","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hybrid Mamba-Transformer with\u00a0Frequency Enhancement for\u00a0Single Image Deraining"],"prefix":"10.1007","author":[{"given":"Yue","family":"Que","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjun","family":"Xia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xue","family":"Xia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"You","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,9]]},"reference":[{"key":"17_CR1","doi-asserted-by":"crossref","unstructured":"Zhou, S., Chen, D., Pan, J., Shi, J., Yang, J.: Adapt or perish: adaptive sparse transformer with attentive feature refinement for image restoration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2952\u20132963 (2024)","DOI":"10.1109\/CVPR52733.2024.00285"},{"issue":"6","key":"17_CR2","doi-asserted-by":"publisher","first-page":"5560","DOI":"10.1109\/TCSVT.2025.3530090","volume":"35","author":"Y Shi","year":"2025","unstructured":"Shi, Y., et al.: VmambaIR: visual state space model for image restoration. IEEE Trans. Circ. Syst. Video Technol. 35(6), 5560\u20135574 (2025)","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"key":"17_CR3","unstructured":"Sun, S., Ren, W., Zhou, J., Gan, J., Wang, R., Cao, X.: A hybrid transformer-mamba network for single image deraining. arXiv preprint arXiv:2409.00410 (2024)"},{"key":"17_CR4","unstructured":"Vaswani, A., et al.: Attention is all you need. Adv. Neural. Inf. Process. Syst. 30 (2017)"},{"key":"17_CR5","first-page":"103031","volume":"37","author":"Y Tian","year":"2024","unstructured":"Tian, Y., et al.: Vmamba: visual state space model. Adv. Neural. Inf. Process. Syst. 37, 103031\u2013103063 (2024)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"17_CR6","doi-asserted-by":"crossref","unstructured":"Huang, T., Pei, X., You, S., Wang, F., Qian, C., Xu, C.: Localmamba: visual state space model with windowed selective scan. In: European Conference on Computer Vision, pp. 12\u201322. Springer (2025)","DOI":"10.1007\/978-3-031-91979-4_2"},{"key":"17_CR7","doi-asserted-by":"crossref","unstructured":"Huang, J., et al.: Exposure normalization and compensation for multiple-exposure correction. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6043\u20136052 (2022)","DOI":"10.1109\/CVPR52688.2022.00595"},{"key":"17_CR8","doi-asserted-by":"crossref","unstructured":"Yamashita, S., Ikehara, M.: Image deraining with frequency-enhanced state space model. In: Proceedings of the Asian Conference on Computer Vision, pp. 3655\u20133671 (2024)","DOI":"10.1007\/978-981-96-0911-6_19"},{"key":"17_CR9","doi-asserted-by":"crossref","unstructured":"Jiang, K., et al.: Multi-scale progressive fusion network for single image deraining. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8346\u20138355 (2020)","DOI":"10.1109\/CVPR42600.2020.00837"},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"Zamir, S.W., et al.: Multi-stage progressive image restoration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14821\u201314831 (2021)","DOI":"10.1109\/CVPR46437.2021.01458"},{"key":"17_CR11","doi-asserted-by":"crossref","unstructured":"Zamir, S.W., Arora, A., Khan, S., Hayat, M., Khan, F.S., Yang, M.-H.: Restormer: efficient transformer for high-resolution image restoration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5728\u20135739 (2022)","DOI":"10.1109\/CVPR52688.2022.00564"},{"key":"17_CR12","doi-asserted-by":"crossref","unstructured":"Chen, X., Li, H., Li, M., Pan, J.: Learning a sparse transformer network for effective image deraining. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5896\u20135905 (2023)","DOI":"10.1109\/CVPR52729.2023.00571"},{"key":"17_CR13","unstructured":"Smith, J.T.H., Warrington, A., Linderman, S.W.: Simplified state space layers for sequence modeling. arXiv preprint arXiv:2208.04933 (2022)"},{"key":"17_CR14","unstructured":"Gu, A., Dao, T.: Mamba: linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.00752 (2023)"},{"key":"17_CR15","doi-asserted-by":"publisher","unstructured":"Guo, H., Li, J., Dai, T., Ouyang, Z., Ren, X., Xia, S.-T.: MambaIR: a simple baseline for image restoration with state-space model. In: Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T., Varol, G. (eds.) ECCV 2024, vol. 15076, pp. 222\u2013241. Springer, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-72649-1_13","DOI":"10.1007\/978-3-031-72649-1_13"},{"key":"17_CR16","doi-asserted-by":"crossref","unstructured":"Shi, W., et al.: Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1874\u20131883 (2016)","DOI":"10.1109\/CVPR.2016.207"},{"key":"17_CR17","doi-asserted-by":"crossref","unstructured":"Liang, J., Cao, J., Sun, G., Zhang, K., Van Gool, L., Timofte, R.: SwinIR: image restoration using swin transformer. In: Proceedings of the IEEE\/CVF Conference on Computer Vision, pp. 1833\u20131844 (2021)","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"17_CR18","doi-asserted-by":"crossref","unstructured":"Fu, X., Huang, J., Zeng, D., Huang, Y., Ding, X., Paisley, J.: Removing rain from single images via a deep detail network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3855\u20133863 (2017)","DOI":"10.1109\/CVPR.2017.186"},{"key":"17_CR19","doi-asserted-by":"crossref","unstructured":"Zhang, H., Patel, V. M.: Density-aware single image de-raining using a multi-stream dense network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 695\u2013704 (2018)","DOI":"10.1109\/CVPR.2018.00079"},{"issue":"11","key":"17_CR20","doi-asserted-by":"publisher","first-page":"3943","DOI":"10.1109\/TCSVT.2019.2920407","volume":"30","author":"H Zhang","year":"2019","unstructured":"Zhang, H., Sindagi, V., Patel, V.M.: Image de-raining using a conditional generative adversarial network. IEEE Trans. Circ. Syst. Video Technol. 30(11), 3943\u20133956 (2019)","journal-title":"IEEE Trans. Circ. Syst. Video Technol."},{"key":"17_CR21","doi-asserted-by":"crossref","unstructured":"Yang, W., Tan, R.T., Feng, J., Liu, J., Guo, Z., Yan, S.: Deep joint rain detection and removal from a single image. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1357\u20131366 (2017)","DOI":"10.1109\/CVPR.2017.183"},{"key":"17_CR22","doi-asserted-by":"crossref","unstructured":"Qian, R., Tan, R.T., Yang, W., Su, J., Liu, J.: Attentive generative adversarial network for raindrop removal from a single image. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2482\u20132491 (2018)","DOI":"10.1109\/CVPR.2018.00263"},{"issue":"6","key":"17_CR23","doi-asserted-by":"publisher","first-page":"2944","DOI":"10.1109\/TIP.2017.2691802","volume":"26","author":"X Fu","year":"2017","unstructured":"Fu, X., Huang, J., Ding, X., Liao, Y., Paisley, J.: Clearing the skies: a deep network architecture for single-image rain removal. IEEE Trans. Image Process. 26(6), 2944\u20132956 (2017)","journal-title":"IEEE Trans. Image Process."},{"key":"17_CR24","doi-asserted-by":"crossref","unstructured":"Wei, W., Meng, D., Zhao, Q., Xu, Z., Wu, Y.: Semi-supervised transfer learning for image rain removal. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3877\u20133886 (2019)","DOI":"10.1109\/CVPR.2019.00400"},{"key":"17_CR25","doi-asserted-by":"crossref","unstructured":"Yasarla, R., Patel, V.M.: Uncertainty guided multi-scale residual learning-using a cycle spinning CNN for single image de-raining. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8405\u20138414 (2019)","DOI":"10.1109\/CVPR.2019.00860"},{"key":"17_CR26","doi-asserted-by":"crossref","unstructured":"Li, X., Wu, J., Lin, Z., Liu, H., Zha, H.: Recurrent squeeze-and-excitation context aggregation net for single image deraining. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 254\u2013269 (2018)","DOI":"10.1007\/978-3-030-01234-2_16"},{"key":"17_CR27","doi-asserted-by":"crossref","unstructured":"Ren, D., Zuo, W., Hu, Q., Zhu, P., Meng, D.: Progressive image deraining networks: a better and simpler baseline. In: Proceedings of the European Conference on Computer Vision, pp. 3937\u20133946 (2019)","DOI":"10.1109\/CVPR.2019.00406"},{"key":"17_CR28","doi-asserted-by":"crossref","unstructured":"Ren, C., Yan, D., Cai, Y., Li, Y.: Semi-swinderain: semi-supervised image deraining network using swin transformer. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1\u20135 (2023)","DOI":"10.1109\/ICASSP49357.2023.10095214"},{"key":"17_CR29","doi-asserted-by":"crossref","unstructured":"Jiang, K., Liu, W., Wang, Z., Zhong, X., Jiang, J., Lin, C.-W.: Dawn: direction-aware attention wavelet network for image deraining. In: Proceedings of the 31st ACM International Conference on Multimedia, pp. 7065\u20137074 (2023)","DOI":"10.1145\/3581783.3611697"},{"key":"17_CR30","doi-asserted-by":"crossref","unstructured":"He, Y., Peng, L., Wang, L., Cheng, J.: Latent degradation representation constraint for single image deraining. In: ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3155\u20133159 (2024)","DOI":"10.1109\/ICASSP48485.2024.10447510"},{"key":"17_CR31","unstructured":"Luo, Z., Gustafsson, F.K., Zhao, Z., Sjolund, J., Schon, T.B.: Controlling vision-language models for multi-task image restoration. arXiv preprint arXiv:2310.01018 (2023)"},{"key":"17_CR32","doi-asserted-by":"crossref","unstructured":"Chen, X., Pan, J., Dong, J.: Bidirectional multi-scale implicit neural representations for image deraining. In: Proceedings of the European Conference on Computer Vision, pp. 25627\u201325636 (2024)","DOI":"10.1109\/CVPR52733.2024.02421"},{"key":"17_CR33","unstructured":"Zhen, Z., Hu, Y., Feng, Z.: FreqMamba: viewing mamba from a frequency perspective for image deraining. arXiv preprint arXiv:2404.09476 (2024)"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5702-8_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T08:29:43Z","timestamp":1767860983000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5702-8_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819557011","9789819557028"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5702-8_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"9 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2025.prcv.cn\/index.asp","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}