{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T00:57:20Z","timestamp":1783385840904,"version":"3.54.6"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T00:00:00Z","timestamp":1772064000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T00:00:00Z","timestamp":1772064000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100017596","name":"Natural Science Basic Research Program of Shaanxi Province","doi-asserted-by":"publisher","award":["No.2024JC-YBMS-527"],"award-info":[{"award-number":["No.2024JC-YBMS-527"]}],"id":[{"id":"10.13039\/501100017596","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Grant No.62573336"],"award-info":[{"award-number":["Grant No.62573336"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1007\/s00371-026-04390-5","type":"journal-article","created":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T13:21:23Z","timestamp":1772112083000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Enhancing self-supervised image denoising with asymmetric mask blind-spot network"],"prefix":"10.1007","volume":"42","author":[{"given":"Yujie","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiwei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaige","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,26]]},"reference":[{"issue":"7","key":"4390_CR1","doi-asserted-by":"publisher","first-page":"3142","DOI":"10.1109\/TIP.2017.2662206","volume":"26","author":"K Zhang","year":"2017","unstructured":"Zhang, K., Zuo, W., Chen, Y., Meng, D., Zhang, L.: Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising. IEEE Trans. Image Process. 26(7), 3142\u20133155 (2017)","journal-title":"IEEE Trans. Image Process."},{"issue":"9","key":"4390_CR2","doi-asserted-by":"publisher","first-page":"4608","DOI":"10.1109\/TIP.2018.2839891","volume":"27","author":"K Zhang","year":"2018","unstructured":"Zhang, K., Zuo, W., Zhang, L.: Ffdnet: Toward a fast and flexible solution for cnn-based image denoising. IEEE Trans. Image Process. 27(9), 4608\u20134622 (2018)","journal-title":"IEEE Trans. Image Process."},{"key":"4390_CR3","doi-asserted-by":"crossref","unstructured":"Guo, S., Yan, Z., Zhang, K., Zuo, W., Zhang, L.: Toward convolutional blind denoising of real photographs. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pages 1712\u20131722, (2019)","DOI":"10.1109\/CVPR.2019.00181"},{"key":"4390_CR4","doi-asserted-by":"crossref","unstructured":"Chen, L., Chu, X., Zhang, X., Sun, J.: Simple baselines for image restoration. In European conference on computer vision, pages 17\u201333. Springer, (2022)","DOI":"10.1007\/978-3-031-20071-7_2"},{"key":"4390_CR5","doi-asserted-by":"crossref","unstructured":"Huang, Y., Huang, H.: Beyond image prior: Embedding noise prior into conditional denoising transformer. arXiv preprint arXiv:2407.09094, (2024)","DOI":"10.1007\/s11263-025-02553-w"},{"key":"4390_CR6","doi-asserted-by":"publisher","first-page":"13074","DOI":"10.1609\/aaai.v34i07.7009","volume":"34","author":"Y Zhou","year":"2020","unstructured":"Zhou, Y., Jiao, J., Huang, H., Wang, Y., Wang, J., Shi, H., Huang, T.: When awgn-based denoiser meets real noises. In Proceedings of the AAAI Conference on Artificial Intelligence 34, 13074\u201313081 (2020)","journal-title":"In Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"4390_CR7","doi-asserted-by":"crossref","unstructured":"Zamir, SW., Arora, A., Khan, S., Hayat, M., Khan, FS., Yang, M.: Restormer: Efficient transformer for high-resolution image restoration. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pages 5728\u20135739, (2022)","DOI":"10.1109\/CVPR52688.2022.00564"},{"key":"4390_CR8","unstructured":"Yue, Z., Yong, H., Zhao, Q., Meng, D., Zhang, L.: Variational denoising network: Toward blind noise modeling and removal. Advances in neural information processing systems, 32, (2019)"},{"key":"4390_CR9","doi-asserted-by":"crossref","unstructured":"Dabov, K., Foi, A., Katkovnik, V.,Egiazarian, K.: Image denoising with block-matching and 3d filtering. In Image processing: algorithms and systems, neural networks, and machine learning, volume 6064, pages 354\u2013365. SPIE, (2006)","DOI":"10.1117\/12.643267"},{"key":"4390_CR10","doi-asserted-by":"crossref","unstructured":"Gu, S., Zhang, L., Zuo, W., Feng, X.: Weighted nuclear norm minimization with application to image denoising. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 2862\u20132869, (2014)","DOI":"10.1109\/CVPR.2014.366"},{"key":"4390_CR11","doi-asserted-by":"crossref","unstructured":"Lee, W., Son, S., Lee, KM.: Ap-bsn: Self-supervised denoising for real-world images via asymmetric pd and blind-spot network. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pages 17725\u201317734, (2022)","DOI":"10.1109\/CVPR52688.2022.01720"},{"key":"4390_CR12","unstructured":"Lehtinen, J., Munkberg, J., Hasselgren, J., Laine, S., Karras, T., Aittala, M.,Aila, T.: Noise2noise: Learning image restoration without clean data. arXiv preprint arXiv:1803.04189, (2018)"},{"key":"4390_CR13","doi-asserted-by":"crossref","unstructured":"Krull, A., Buchholz, T., Jug, F.: Noise2void-learning denoising from single noisy images. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pages 2129\u20132137, (2019)","DOI":"10.1109\/CVPR.2019.00223"},{"key":"4390_CR14","unstructured":"Batson, J., Royer, L.: Noise2self: Blind denoising by self-supervision. In International conference on machine learning, pages 524\u2013533. PMLR, (2019)"},{"key":"4390_CR15","doi-asserted-by":"crossref","unstructured":"Neshatavar, R.,Yavartanoo, M., Son, S., Lee, KM.: Cvf-sid: Cyclic multi-variate function for self-supervised image denoising by disentangling noise from image. In Proceedings of the ieee\/cvf Conference on Computer Vision and Pattern Recognition, pages 17583\u201317591, (2022)","DOI":"10.1109\/CVPR52688.2022.01706"},{"key":"4390_CR16","doi-asserted-by":"crossref","unstructured":"Li, J., Zhang, Z., Liu, X., Feng, C., Wang, X., Lei, L., Zuo, W.: Spatially adaptive self-supervised learning for real-world image denoising. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pages 9914\u20139924, (2023)","DOI":"10.1109\/CVPR52729.2023.00956"},{"key":"4390_CR17","doi-asserted-by":"crossref","unstructured":"Zhang, D., Zhou, F., Jiang, Y., Fu, Z.: Mm-bsn: Self-supervised image denoising for real-world with multi-mask based on blind-spot network. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pages 4189\u20134198, (2023)","DOI":"10.1109\/CVPRW59228.2023.00441"},{"issue":"10","key":"4390_CR18","doi-asserted-by":"publisher","first-page":"10107","DOI":"10.1109\/TCSVT.2024.3402095","volume":"34","author":"L Fan","year":"2024","unstructured":"Fan, L., Cui, J., Li, H., Yan, X., Liu, H., Zhang, C.: Complementary blind-spot network for self-supervised real image denoising. IEEE Trans. Circuits Syst. Video Technol. 34(10), 10107\u201310120 (2024)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"4390_CR19","doi-asserted-by":"crossref","unstructured":"Wang, R., Jiang, Y.: Effective enhancement and fusion of multi-perspective features for self-supervised real image denoising. The Visual Computer, Jun 2025","DOI":"10.1007\/s00371-025-04009-1"},{"key":"4390_CR20","doi-asserted-by":"publisher","first-page":"25090","DOI":"10.1109\/ACCESS.2024.3364397","volume":"12","author":"KS Panigrahi","year":"2024","unstructured":"Panigrahi, K.S., Tripathy, S.K., Bhowmick, A., Satapathy, S.K., Barsocchi, P., Bhoi, A.K.: Multi-scale based approach for denoising real-world noisy image using curvelet thresholding. IEEE Access 12, 25090\u201325105 (2024)","journal-title":"IEEE Access"},{"key":"4390_CR21","doi-asserted-by":"crossref","unstructured":"Chatterjee, P., Joshi, N., Kang, SB., Matsushita, Y.: Noise suppression in low-light images through joint denoising and demosaicing. In CVPR 2011, pages 321\u2013328. IEEE, 2011","DOI":"10.1109\/CVPR.2011.5995371"},{"key":"4390_CR22","doi-asserted-by":"crossref","unstructured":"Jin, Q., Facciolo, G., Morel, J.: A review of an old dilemma: Demosaicking first, or denoising first? In proceedings of the IEEE\/CVF conference on computer vision and pattern recognition workshops, pages 514\u2013515, 2020","DOI":"10.1109\/CVPRW50498.2020.00265"},{"key":"4390_CR23","doi-asserted-by":"crossref","unstructured":"Park, SH., Kim, HS., Lansel, S., Parmar, M., Wandell, BA.: A case for denoising before demosaicking color filter array data. In 2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers, pages 860\u2013864. IEEE, 2009","DOI":"10.1109\/ACSSC.2009.5469990"},{"key":"4390_CR24","doi-asserted-by":"crossref","unstructured":"Wang Z, Fu, Y., Liu, J., Zhang, Y.: Lg-bpn: Local and global blind-patch network for self-supervised real-world denoising. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pages 18156\u201318165, 2023","DOI":"10.1109\/CVPR52729.2023.01741"},{"key":"4390_CR25","doi-asserted-by":"publisher","first-page":"13074","DOI":"10.1609\/aaai.v34i07.7009","volume":"34","author":"Y Zhou","year":"2020","unstructured":"Zhou, Y., Jiao, J., Huang, H., Wang, Y., Wang, J., Shi, H., Huang, T.: When awgn-based denoiser meets real noises. In Proceedings of the AAAI Conference on Artificial Intelligence 34, 13074\u201313081 (2020)","journal-title":"In Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"4390_CR26","doi-asserted-by":"crossref","unstructured":"Pan, Y., Liu, X., Liao, X., Cao, Y., Ren, C.: Random sub-samples generation for self-supervised real image denoising. In Proceedings of the IEEE\/CVF International Conference on Computer Vision, pages 12150\u201312159, 2023","DOI":"10.1109\/ICCV51070.2023.01116"},{"key":"4390_CR27","doi-asserted-by":"publisher","first-page":"4788","DOI":"10.1609\/aaai.v39i5.32506","volume":"39","author":"J Li","year":"2025","unstructured":"Li, J., Zhang, Z., Zuo, W.: Rethinking transformer-based blind-spot network for self-supervised image denoising. In Proceedings of the AAAI Conference on Artificial Intelligence 39, 4788\u20134796 (2025)","journal-title":"In Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"4390_CR28","first-page":"19217","volume":"36","author":"H Jang","year":"2023","unstructured":"Jang, H., Park, J., Jung, D., Lew, J., Bae, H., Yoon, S.: Puca: patch-unshuffle and channel attention for enhanced self-supervised image denoising. Adv. Neural. Inf. Process. Syst. 36, 19217\u201319229 (2023)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"4390_CR29","doi-asserted-by":"publisher","first-page":"49720","DOI":"10.1109\/ACCESS.2024.3384577","volume":"12","author":"H Tang","year":"2024","unstructured":"Tang, H., Zhang, W., Zhu, H., Zhao, K.: Self-supervised real-world image denoising based on multi-scale feature enhancement and attention fusion. IEEE Access 12, 49720\u201349734 (2024)","journal-title":"IEEE Access"},{"key":"4390_CR30","doi-asserted-by":"publisher","first-page":"14340","DOI":"10.1109\/ACCESS.2023.3243829","volume":"11","author":"D Zhang","year":"2023","unstructured":"Zhang, D., Zhou, F.: Self-supervised image denoising for real-world images with context-aware transformer. IEEE Access 11, 14340\u201314349 (2023)","journal-title":"IEEE Access"},{"key":"4390_CR31","doi-asserted-by":"crossref","unstructured":"Abdelhamed, A., Lin, S., Brown, MS.: A high-quality denoising dataset for smartphone cameras. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 1692\u20131700, 2018","DOI":"10.1109\/CVPR.2018.00182"},{"key":"4390_CR32","doi-asserted-by":"crossref","unstructured":"Plotz, T., Roth, S.: Benchmarking denoising algorithms with real photographs. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 1586\u20131595, 2017","DOI":"10.1109\/CVPR.2017.294"},{"key":"4390_CR33","doi-asserted-by":"crossref","unstructured":"Huang, T., Li, S., Jia, X., Lu, H., Liu, J.: Neighbor2neighbor: Self-supervised denoising from single noisy images. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pages 14781\u201314790, 2021","DOI":"10.1109\/CVPR46437.2021.01454"},{"key":"4390_CR34","doi-asserted-by":"crossref","unstructured":"Mansour, Y., Heckel, R.: Zero-shot noise2noise: Efficient image denoising without any data. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pages 14018\u201314027, 2023","DOI":"10.1109\/CVPR52729.2023.01347"},{"key":"4390_CR35","doi-asserted-by":"crossref","unstructured":"Pang, T., Zheng, H., Quan, Y.,Ji, H.: Recorrupted-to-recorrupted: Unsupervised deep learning for image denoising. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pages 2043\u20132052, 2021","DOI":"10.1109\/CVPR46437.2021.00208"},{"key":"4390_CR36","unstructured":"Laine, S., Karras, T., Lehtinen, J.,Aila, T.: High-quality self-supervised deep image denoising. In H.\u00a0Wallach, H.\u00a0Larochelle, A.\u00a0Beygelzimer, F.\u00a0d\u2019 Alch\u00e9-Buc, E.\u00a0Fox, and R.\u00a0Garnett, editors, Advances in Neural Information Processing Systems, volume\u00a032. Curran Associates, Inc., 2019"},{"key":"4390_CR37","doi-asserted-by":"crossref","unstructured":"Wu, X., Liu, M., Cao, Y., Ren, D., Zuo, W.: Unpaired learning of deep image denoising. In European conference on computer vision, pages 352\u2013368. Springer, 2020","DOI":"10.1007\/978-3-030-58548-8_21"},{"key":"4390_CR38","doi-asserted-by":"crossref","unstructured":"Wang, Z., Liu, J., Li, G., Han, H.: Blind2unblind: Self-supervised image denoising with visible blind spots. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pages 2027\u20132036, 2022","DOI":"10.1109\/CVPR52688.2022.00207"},{"key":"4390_CR39","doi-asserted-by":"crossref","unstructured":"Brummer, B.,Vleeschouwer, C.D.: Natural image noise dataset. In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pages 1777\u20131784, 2019","DOI":"10.1109\/CVPRW.2019.00228"},{"key":"4390_CR40","doi-asserted-by":"publisher","first-page":"9316","DOI":"10.1109\/TIP.2020.3026622","volume":"29","author":"X Jun","year":"2020","unstructured":"Jun, X., Huang, Y., Cheng, M.-M., Liu, L., Zhu, F., Zhou, X., Shao, L.: Noisy-as-clean: Learning self-supervised denoising from corrupted image. IEEE Trans. Image Process. 29, 9316\u20139329 (2020)","journal-title":"IEEE Trans. Image Process."}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-026-04390-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-026-04390-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-026-04390-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T16:20:48Z","timestamp":1774455648000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-026-04390-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,26]]},"references-count":40,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["4390"],"URL":"https:\/\/doi.org\/10.1007\/s00371-026-04390-5","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,26]]},"assertion":[{"value":"10 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 January 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 February 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"183"}}