{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T00:37:20Z","timestamp":1770424640071,"version":"3.49.0"},"reference-count":58,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T00:00:00Z","timestamp":1734307200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T00:00:00Z","timestamp":1734307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62376285"],"award-info":[{"award-number":["62376285"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1007\/s10489-024-06050-4","type":"journal-article","created":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T10:06:44Z","timestamp":1734343604000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Prompt-guided and degradation prior supervised transformer for adverse weather image restoration"],"prefix":"10.1007","volume":"55","author":[{"given":"Weihan","family":"Liu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7323-5896","authenticated-orcid":false,"given":"Mingwen","family":"Shao","sequence":"additional","affiliation":[]},{"given":"Lingzhuang","family":"Meng","sequence":"additional","affiliation":[]},{"given":"Yuanjian","family":"Qiao","sequence":"additional","affiliation":[]},{"given":"Zhiyuan","family":"Bao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,16]]},"reference":[{"key":"6050_CR1","doi-asserted-by":"crossref","unstructured":"Charbonnier P, Blanc-Feraud L, Aubert G et\u00a0al (1994) Two deterministic half-quadratic regularization algorithms for computed imaging. In: Proceedings of 1st international conference on image processing. IEEE, pp 168\u2013172","DOI":"10.1109\/ICIP.1994.413553"},{"key":"6050_CR2","doi-asserted-by":"crossref","unstructured":"Chen H, Wang Y, Guo T et\u00a0al (2021) Pre-trained image processing transformer. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 12299\u201312310","DOI":"10.1109\/CVPR46437.2021.01212"},{"key":"6050_CR3","doi-asserted-by":"crossref","unstructured":"Chen L, Chu X, Zhang X et\u00a0al (2022) Simple baselines for image restoration. In: European conference on computer vision. Springer, pp 17\u201333","DOI":"10.1007\/978-3-031-20071-7_2"},{"key":"6050_CR4","doi-asserted-by":"crossref","unstructured":"Chen W, Fang H, Hsieh CL et\u00a0al (2021) All snow removed: Single image desnowing algorithm using hierarchical dual-tree complex wavelet representation and contradict channel loss. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 4196\u20134205","DOI":"10.1109\/ICCV48922.2021.00416"},{"key":"6050_CR5","doi-asserted-by":"crossref","unstructured":"Chen W, Huang Z, Tsai CC et\u00a0al (2022) Learning multiple adverse weather removal via two-stage knowledge learning and multi-contrastive regularization: Toward a unified model. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 17653\u201317662","DOI":"10.1109\/CVPR52688.2022.01713"},{"key":"6050_CR6","doi-asserted-by":"crossref","unstructured":"Chen X, Pan J, Jiang K et\u00a0al (2022) Unpaired deep image deraining using dual contrastive learning. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 2017\u20132026","DOI":"10.1109\/CVPR52688.2022.00206"},{"key":"6050_CR7","doi-asserted-by":"crossref","unstructured":"Chen X, Li H, Li M et\u00a0al (2023) 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","DOI":"10.1109\/CVPR52729.2023.00571"},{"key":"6050_CR8","unstructured":"Dosovitskiy A, Beyer L, Kolesnikov A et\u00a0al (2020) An image is worth 16x16 words: Transformers for image recognition at scale. In: International conference on learning representations"},{"key":"6050_CR9","doi-asserted-by":"crossref","unstructured":"Fu X, Huang J, Zeng D et\u00a0al (2017) 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","DOI":"10.1109\/CVPR.2017.186"},{"key":"6050_CR10","doi-asserted-by":"crossref","unstructured":"Gao T, Wen Y, Zhang K et\u00a0al (2023) Towards an effective and efficient transformer for rain-by-snow weather removal. Available at SSRN 4458244","DOI":"10.2139\/ssrn.4458244"},{"key":"6050_CR11","doi-asserted-by":"crossref","unstructured":"Ghahremannezhad H, Shi H, Liu C (2023) Object detection in traffic videos: A survey. IEEE Trans Intell Transp Syst","DOI":"10.36227\/techrxiv.20477685.v1"},{"key":"6050_CR12","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1007\/s41095-021-0229-5","volume":"7","author":"M Guo","year":"2021","unstructured":"Guo M, Cai J, Liu Z et al (2021) Pct: Point cloud transformer. Comput Vis Med 7:187\u2013199","journal-title":"Comput Vis Med"},{"key":"6050_CR13","doi-asserted-by":"crossref","unstructured":"Han L, Yin Z (2022) Global memory and local continuity for video object detection. IEEE Trans Multimed","DOI":"10.1109\/TMM.2022.3164253"},{"issue":"3","key":"6050_CR14","doi-asserted-by":"publisher","first-page":"3446","DOI":"10.1109\/TPAMI.2022.3180560","volume":"45","author":"H Huang","year":"2022","unstructured":"Huang H, Luo M, He R (2022) Memory uncertainty learning for real-world single image deraining. IEEE Trans Pattern Anal Mach Intell 45(3):3446\u20133460","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"13","key":"6050_CR15","doi-asserted-by":"publisher","first-page":"800","DOI":"10.1049\/el:20080522","volume":"44","author":"Q Huynh-Thu","year":"2008","unstructured":"Huynh-Thu Q, Ghanbari M (2008) Scope of validity of psnr in image\/video quality assessment. Electron Lett 44(13):800\u2013801","journal-title":"Electron Lett"},{"issue":"4","key":"6050_CR16","doi-asserted-by":"publisher","first-page":"1342","DOI":"10.1109\/TCSVT.2020.3003025","volume":"31","author":"DW Jaw","year":"2020","unstructured":"Jaw DW, Huang SC, Kuo SY (2020) Desnowgan: An efficient single image snow removal framework using cross-resolution lateral connection and gans. IEEE Trans Circ Syst Video Technol 31(4):1342\u20131350","journal-title":"IEEE Trans Circ Syst Video Technol"},{"key":"6050_CR17","first-page":"14745","volume":"34","author":"Y Jiang","year":"2021","unstructured":"Jiang Y, Chang S, Wang Z (2021) Transgan: Two pure transformers can make one strong gan, and that can scale up. Adv Neural Inf Process Syst 34:14745\u201314758","journal-title":"Adv Neural Inf Process Syst"},{"issue":"4","key":"6050_CR18","doi-asserted-by":"publisher","first-page":"1742","DOI":"10.1109\/TIP.2011.2179057","volume":"21","author":"L Kang","year":"2011","unstructured":"Kang L, Lin CW, Fu YH (2011) Automatic single-image-based rain streaks removal via image decomposition. IEEE Trans Image Process 21(4):1742\u20131755","journal-title":"IEEE Trans Image Process"},{"key":"6050_CR19","doi-asserted-by":"crossref","unstructured":"Li B, Liu X, Hu P et\u00a0al (2022) All-in-one image restoration for unknown corruption. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 17452\u201317462","DOI":"10.1109\/CVPR52688.2022.01693"},{"key":"6050_CR20","doi-asserted-by":"crossref","unstructured":"Li R, Cheong LF, Tan RT (2019) Heavy rain image restoration: Integrating physics model and conditional adversarial learning. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 1633\u20131642","DOI":"10.1109\/CVPR.2019.00173"},{"key":"6050_CR21","doi-asserted-by":"crossref","unstructured":"Li R, Tan RT, Cheong LF (2020) All in one bad weather removal using architectural search. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 3175\u20133185","DOI":"10.1109\/CVPR42600.2020.00324"},{"key":"6050_CR22","doi-asserted-by":"crossref","unstructured":"Liang J, Cao J, Sun G et\u00a0al (2021) Swinir: Image restoration using swin transformer. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 1833\u20131844","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"6050_CR23","doi-asserted-by":"crossref","unstructured":"Lin J, Jiang N, Zhang Z et\u00a0al (2023) Lmqformer: A laplace-prior-guided mask query transformer for lightweight snow removal. IEEE Trans Circ Syst Video Technol","DOI":"10.1109\/TCSVT.2023.3264824"},{"key":"6050_CR24","doi-asserted-by":"crossref","unstructured":"Liu L, Xie L, Zhang X et\u00a0al (2022) Tape: Task-agnostic prior embedding for image restoration. In: European conference on computer vision. Springer, pp 447\u2013464","DOI":"10.1007\/978-3-031-19797-0_26"},{"key":"6050_CR25","doi-asserted-by":"crossref","unstructured":"Liu X, Suganuma M, Sun Z et\u00a0al (2019) Dual residual networks leveraging the potential of paired operations for image restoration. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 7007\u20137016","DOI":"10.1109\/CVPR.2019.00717"},{"issue":"6","key":"6050_CR26","doi-asserted-by":"publisher","first-page":"3064","DOI":"10.1109\/TIP.2018.2806202","volume":"27","author":"Y Liu","year":"2018","unstructured":"Liu Y, Jaw DW, Huang SC et al (2018) Desnownet: Context-aware deep network for snow removal. IEEE Trans Image Process 27(6):3064\u20133073","journal-title":"IEEE Trans Image Process"},{"key":"6050_CR27","doi-asserted-by":"publisher","first-page":"110986","DOI":"10.1016\/j.knosys.2023.110986","volume":"280","author":"Y Liu","year":"2023","unstructured":"Liu Y, Yang D, Fang G et al (2023) Stochastic video normality network for abnormal event detection in surveillance videos. Knowl-Based Syst 280:110986","journal-title":"Knowl-Based Syst"},{"key":"6050_CR28","doi-asserted-by":"crossref","unstructured":"Liu Z, Ning J, Cao Y et\u00a0al (2022) Video swin transformer. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 3202\u20133211","DOI":"10.1109\/CVPR52688.2022.00320"},{"key":"6050_CR29","unstructured":"Luo Z, Gustafsson FK, Zhao Z et\u00a0al (2023) Controlling vision-language models for universal image restoration. In: The Twelfth international conference on learning representations"},{"key":"6050_CR30","doi-asserted-by":"crossref","unstructured":"\u00d6zdenizci O, Legenstein R (2023) Restoring vision in adverse weather conditions with patch-based denoising diffusion models. IEEE Trans Pattern Anal Mach Intell","DOI":"10.1109\/TPAMI.2023.3238179"},{"key":"6050_CR31","unstructured":"Potlapalli V, Zamir SW, Khan S et\u00a0al (2023) Promptir: Prompting for all-in-one image restoration. In: Advances in Neural Information Processing Systems"},{"key":"6050_CR32","doi-asserted-by":"crossref","unstructured":"Purohit K, Suin M, Rajagopalan A et\u00a0al (2021) Spatially-adaptive image restoration using distortion-guided networks. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 2309\u20132319","DOI":"10.1109\/ICCV48922.2021.00231"},{"key":"6050_CR33","doi-asserted-by":"crossref","unstructured":"Qian R, Tan RT, Yang W et\u00a0al (2018) 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","DOI":"10.1109\/CVPR.2018.00263"},{"key":"6050_CR34","doi-asserted-by":"crossref","unstructured":"Quan R, Yu X, Liang Y et\u00a0al (2021) Removing raindrops and rain streaks in one go. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 9147\u20139156","DOI":"10.1109\/CVPR46437.2021.00903"},{"key":"6050_CR35","unstructured":"Radford A, Kim JW, Hallacy C et\u00a0al (2021) Learning transferable visual models from natural language supervision. In: International conference on machine learning, PMLR, pp 8748\u20138763"},{"key":"6050_CR36","doi-asserted-by":"crossref","unstructured":"Ren D, Zuo W, Hu Q et\u00a0al (2019) Progressive image deraining networks: A better and simpler baseline. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 3937\u20133946","DOI":"10.1109\/CVPR.2019.00406"},{"key":"6050_CR37","doi-asserted-by":"publisher","first-page":"4828","DOI":"10.1109\/TIP.2021.3076283","volume":"30","author":"M Shao","year":"2021","unstructured":"Shao M, Li L, Meng D et al (2021) Uncertainty guided multi-scale attention network for raindrop removal from a single image. IEEE Trans Image Process 30:4828\u20134839","journal-title":"IEEE Trans Image Process"},{"key":"6050_CR38","doi-asserted-by":"publisher","first-page":"110306","DOI":"10.1016\/j.knosys.2023.110306","volume":"263","author":"M Shao","year":"2023","unstructured":"Shao M, Qiao Y, Meng D et al (2023) Uncertainty-guided hierarchical frequency domain transformer for image restoration. Knowl-Based Syst 263:110306","journal-title":"Knowl-Based Syst"},{"key":"6050_CR39","doi-asserted-by":"crossref","unstructured":"Tan Z, Wu Y, Liu Q et\u00a0al (2024) Exploring the application of large-scale pre-trained models on adverse weather removal. IEEE Trans Image Process","DOI":"10.1109\/TIP.2024.3368961"},{"key":"6050_CR40","doi-asserted-by":"crossref","unstructured":"Valanarasu JMJ, Oza P, Hacihaliloglu I et\u00a0al (2021) Medical transformer: Gated axial-attention for medical image segmentation. In: Medical Image Computing and Computer Assisted Intervention\u2013MICCAI 2021: 24th International Conference, Strasbourg, France, September 27\u2013October 1, 2021, Proceedings, Part I 24, Springer, pp 36\u201346","DOI":"10.1007\/978-3-030-87193-2_4"},{"key":"6050_CR41","doi-asserted-by":"crossref","unstructured":"Valanarasu JMJ, Yasarla R, Patel VM (2022) Transweather: Transformer-based restoration of images degraded by adverse weather conditions. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 2353\u20132363","DOI":"10.1109\/CVPR52688.2022.00239"},{"key":"6050_CR42","unstructured":"Vaswani A, Shazeer N, Parmar N et\u00a0al (2017) Attention is all you need. Advances in Neural Information Processing Systems, vol 30"},{"key":"6050_CR43","doi-asserted-by":"publisher","first-page":"109244","DOI":"10.1016\/j.knosys.2022.109244","volume":"252","author":"Y Wan","year":"2022","unstructured":"Wan Y, Cheng Y, Shao M et al (2022) Image rain removal and illumination enhancement done in one go. Knowl-Based Syst 252:109244","journal-title":"Knowl-Based Syst"},{"key":"6050_CR44","doi-asserted-by":"publisher","first-page":"111116","DOI":"10.1016\/j.knosys.2023.111116","volume":"282","author":"X Wang","year":"2023","unstructured":"Wang X, Chen H, Gou H et al (2023) Restornet: An efficient network for multiple degradation image restoration. Knowl-Based Syst 282:111116","journal-title":"Knowl-Based Syst"},{"key":"6050_CR45","doi-asserted-by":"crossref","unstructured":"Wang Y, Ye H, Cao F (2022) A novel multi-discriminator deep network for image segmentation. Appl Intell 1\u201318","DOI":"10.1007\/s10489-021-02427-x"},{"issue":"4","key":"6050_CR46","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang Z, Bovik AC, Sheikh HR et al (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600\u2013612","journal-title":"IEEE Trans Image Process"},{"key":"6050_CR47","doi-asserted-by":"crossref","unstructured":"Wang Z, Cun X, Bao J et\u00a0al (2022) Uformer: A general u-shaped transformer for image restoration. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 17683\u201317693","DOI":"10.1109\/CVPR52688.2022.01716"},{"key":"6050_CR48","doi-asserted-by":"crossref","unstructured":"Xue Y, Yao W, Peng S et\u00a0al (2023) Automatic filter pruning algorithm for image classification. Appl Intell 1\u201315","DOI":"10.1007\/s10489-023-05207-x"},{"key":"6050_CR49","doi-asserted-by":"crossref","unstructured":"Yang H, Guo J, Xin Y et\u00a0al (2023) Multi-scale fusion and adaptively attentive generative adversarial network for image de-raining. Appl Intell 1\u201317","DOI":"10.1007\/s10489-023-05114-1"},{"key":"6050_CR50","doi-asserted-by":"crossref","unstructured":"Yang W, Tan RT, Feng J et\u00a0al (2017) Deep joint rain detection and removal from a single image. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 1357\u20131366","DOI":"10.1109\/CVPR.2017.183"},{"issue":"5","key":"6050_CR51","first-page":"5951","volume":"53","author":"Y Yang","year":"2023","unstructured":"Yang Y, Zhang H, Wu X et al (2023) Mstfdn: Multi-scale transformer fusion dehazing network. Appl Intell 53(5):5951\u20135962","journal-title":"Appl Intell"},{"key":"6050_CR52","doi-asserted-by":"crossref","unstructured":"Yasarla R, Patel VM (2019) 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","DOI":"10.1109\/CVPR.2019.00860"},{"key":"6050_CR53","doi-asserted-by":"crossref","unstructured":"Yue W, Zhou Z, Cao Y et\u00a0al (2023) Visual representations with texts domain generalization for semantic segmentation. Appl Intell 1\u201311","DOI":"10.1007\/s10489-023-05125-y"},{"key":"6050_CR54","doi-asserted-by":"crossref","unstructured":"Zamir SW, Arora A, Khan S et\u00a0al (2021) Multi-stage progressive image restoration. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 14821\u201314831","DOI":"10.1109\/CVPR46437.2021.01458"},{"key":"6050_CR55","doi-asserted-by":"crossref","unstructured":"Zamir SW, Arora A, Khan S et\u00a0al (2022) Restormer: Efficient transformer for high-resolution image restoration. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 5728\u20135739","DOI":"10.1109\/CVPR52688.2022.00564"},{"key":"6050_CR56","doi-asserted-by":"crossref","unstructured":"Zhang C, Zhu Y, Yan Q et\u00a0al (2023) All-in-one multi-degradation image restoration network via hierarchical degradation representation. In: Proceedings of the 31st ACM international conference on multimedia, pp 2285\u20132293","DOI":"10.1145\/3581783.3611825"},{"key":"6050_CR57","doi-asserted-by":"publisher","first-page":"7419","DOI":"10.1109\/TIP.2021.3104166","volume":"30","author":"K Zhang","year":"2021","unstructured":"Zhang K, Li R, Yu Y et al (2021) Deep dense multi-scale network for snow removal using semantic and depth priors. IEEE Trans Image Process 30:7419\u20137431","journal-title":"IEEE Trans Image Process"},{"key":"6050_CR58","doi-asserted-by":"crossref","unstructured":"Zhu Y, Wang T, Fu X et\u00a0al (2023) Learning weather-general and weather-specific features for image restoration under multiple adverse weather conditions. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 21747\u201321758","DOI":"10.1109\/CVPR52729.2023.02083"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-06050-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-024-06050-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-06050-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,30]],"date-time":"2025-01-30T16:03:57Z","timestamp":1738253037000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-024-06050-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,16]]},"references-count":58,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["6050"],"URL":"https:\/\/doi.org\/10.1007\/s10489-024-06050-4","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,16]]},"assertion":[{"value":"6 September 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 December 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors have no relevant financial or non-financial interests to disclose.  The authors have no competing interests to declare that are relevant to the content of this article.  All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.  The authors have no financial or proprietary interests in any material discussed in this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"172"}}