{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T20:27:49Z","timestamp":1768681669554,"version":"3.49.0"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"14","license":[{"start":{"date-parts":[[2024,2,27]],"date-time":"2024-02-27T00:00:00Z","timestamp":1708992000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,2,27]],"date-time":"2024-02-27T00:00:00Z","timestamp":1708992000000},"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":["Neural Comput & Applic"],"published-print":{"date-parts":[[2024,5]]},"DOI":"10.1007\/s00521-024-09478-4","type":"journal-article","created":{"date-parts":[[2024,2,27]],"date-time":"2024-02-27T19:02:19Z","timestamp":1709060539000},"page":"8039-8053","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Contrastive feature decomposition for single image layer separation"],"prefix":"10.1007","volume":"36","author":[{"given":"Xin","family":"Feng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyuan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haobo","family":"Ji","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenjie","family":"Pei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1578-2634","authenticated-orcid":false,"given":"Guangming","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,2,27]]},"reference":[{"key":"9478_CR1","doi-asserted-by":"crossref","unstructured":"Fan Q, Yang J, Hua G, Chen B, Wipf D (2017) A generic deep architecture for single image reflection removal and image smoothing. In: Proceedings of the IEEE international conference on computer vision, pp 3238\u20133247","DOI":"10.1109\/ICCV.2017.351"},{"issue":"9","key":"9478_CR2","doi-asserted-by":"publisher","first-page":"1647","DOI":"10.1109\/TPAMI.2007.1106","volume":"29","author":"A Levin","year":"2007","unstructured":"Levin A, Weiss Y (2007) User assisted separation of reflections from a single image using a sparsity prior. IEEE Trans Pattern Anal Mach Intell 29(9):1647\u20131654","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9478_CR3","doi-asserted-by":"crossref","unstructured":"Wan R, Shi B, Hwee TA, Kot AC (2016) Depth of field guided reflection removal. In: 2016 IEEE international conference on image processing (ICIP). IEEE, pp 21\u201325","DOI":"10.1109\/ICIP.2016.7532311"},{"issue":"10","key":"9478_CR4","doi-asserted-by":"publisher","first-page":"1173","DOI":"10.1109\/LSP.2014.2327071","volume":"21","author":"Q Yan","year":"2014","unstructured":"Yan Q, Xu Y, Yang X, Nguyen T (2014) Separation of weak reflection from a single superimposed image. IEEE Signal Process Lett 21(10):1173\u20131176","journal-title":"IEEE Signal Process Lett"},{"key":"9478_CR5","doi-asserted-by":"crossref","unstructured":"Arvanitopoulos N, Achanta R, Susstrunk S (2017) Single image reflection suppression. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4498\u20134506","DOI":"10.1109\/CVPR.2017.190"},{"key":"9478_CR6","doi-asserted-by":"crossref","unstructured":"Li C, Yang Y, He K, Lin S, Hopcroft JE (2020) Single image reflection removal through cascaded refinement. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 3565\u20133574","DOI":"10.1109\/CVPR42600.2020.00362"},{"key":"9478_CR7","doi-asserted-by":"crossref","unstructured":"Wen Q, Tan Y, Qin J, Liu W, Han G, He S (2019) Single image reflection removal beyond linearity. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3771\u20133779","DOI":"10.1109\/CVPR.2019.00389"},{"key":"9478_CR8","doi-asserted-by":"crossref","unstructured":"Wei K, Yang J, Fu Y, Wipf D, Huang H (2019) Single image reflection removal exploiting misaligned training data and network enhancements. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 8178\u20138187","DOI":"10.1109\/CVPR.2019.00837"},{"key":"9478_CR9","doi-asserted-by":"crossref","unstructured":"Yang J, Gong D, Liu L, Shi Q (2018) Seeing deeply and bidirectionally: a deep learning approach for single image reflection removal. In: Proceedings of the European conference on computer vision, pp 654\u2013669","DOI":"10.1007\/978-3-030-01219-9_40"},{"key":"9478_CR10","doi-asserted-by":"publisher","first-page":"4867","DOI":"10.1109\/TIP.2021.3076589","volume":"30","author":"X Feng","year":"2021","unstructured":"Feng X, Pei W, Jia Z, Chen F, Zhang D, Lu G (2021) Deep-masking generative network: a unified framework for background restoration from superimposed images. IEEE Trans Image Process 30:4867\u20134882","journal-title":"IEEE Trans Image Process"},{"key":"9478_CR11","doi-asserted-by":"crossref","unstructured":"Zou Z, Lei S, Shi T, Shi Z, Ye J (2020) Deep adversarial decomposition: a unified framework for separating superimposed images. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 12806\u201312816","DOI":"10.1109\/CVPR42600.2020.01282"},{"key":"9478_CR12","doi-asserted-by":"crossref","unstructured":"Feng X, Ji H, Jiang B, Pei W, Chen F, Lu G (2021) Contrastive feature decomposition for image reflection removal. In: 2021 IEEE international conference on multimedia and expo. IEEE, pp 1\u20136","DOI":"10.1109\/ICME51207.2021.9428089"},{"key":"9478_CR13","doi-asserted-by":"crossref","unstructured":"Wan R, Shi B, Tan A-H, Kot AC (2017) Sparsity based reflection removal using external patch search. In: 2017 IEEE international conference on multimedia and expo (ICME). IEEE, pp 1500\u20131505","DOI":"10.1109\/ICME.2017.8019527"},{"issue":"14","key":"9478_CR14","doi-asserted-by":"publisher","first-page":"8543","DOI":"10.1007\/s00521-020-05606-y","volume":"33","author":"S Ma","year":"2021","unstructured":"Ma S, Zhang H, Miao Z (2021) Blind source separation for the analysis sparse model. Neural Comput Appl 33(14):8543\u20138553","journal-title":"Neural Comput Appl"},{"issue":"19","key":"9478_CR15","doi-asserted-by":"publisher","first-page":"16223","DOI":"10.1007\/s00521-022-07315-0","volume":"34","author":"C Li","year":"2022","unstructured":"Li C, He W, Liao N, Gong J, Hou S, Guo B (2022) Superpixels with contour adherence via label expansion for image decomposition. Neural Comput Appl 34(19):16223\u201316237","journal-title":"Neural Comput Appl"},{"key":"9478_CR16","unstructured":"Shen L, Tan P, Lin S (2008) Intrinsic image decomposition with non-local texture cues. In: 2008 IEEE conference on computer vision and pattern recognition. IEEE, pp 1\u20137"},{"key":"9478_CR17","doi-asserted-by":"crossref","unstructured":"Chen Q, Koltun V (2013) A simple model for intrinsic image decomposition with depth cues. In: Proceedings of the IEEE international conference on computer vision, pp 241\u2013248","DOI":"10.1109\/ICCV.2013.37"},{"key":"9478_CR18","unstructured":"Shih Y, Krishnan D, Durand F, Freeman WT (2015) Reflection removal using ghosting cues. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3193\u20133201"},{"key":"9478_CR19","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1109\/TCI.2019.2899320","volume":"6","author":"Y Huang","year":"2019","unstructured":"Huang Y, Quan Y, Xu Y, Xu R, Ji H (2019) Removing reflection from a single image with ghosting effect. IEEE Trans Comput Imaging 6:34\u201345","journal-title":"IEEE Trans Comput Imaging"},{"key":"9478_CR20","doi-asserted-by":"crossref","unstructured":"Yang, Y, Ma W, Zheng Y, Cai J-F, Xu W (2019) Fast single image reflection suppression via convex optimization. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 8141\u20138149","DOI":"10.1109\/CVPR.2019.00833"},{"key":"9478_CR21","doi-asserted-by":"crossref","unstructured":"Zhang X, Ng R, Chen Q (2018) Single image reflection separation with perceptual losses. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4786\u20134794","DOI":"10.1109\/CVPR.2018.00503"},{"key":"9478_CR22","doi-asserted-by":"crossref","unstructured":"Fan Q, Yang J, Hua G, Chen B, Wipf D (2018) Revisiting deep intrinsic image decompositions. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 8944\u20138952","DOI":"10.1109\/CVPR.2018.00932"},{"key":"9478_CR23","doi-asserted-by":"crossref","unstructured":"Wang C, Xu D, Wan R, He B, Shi B, Duan L-Y (2022) Background scene recovery from an image looking through colored glass. IEEE Trans Multimedia","DOI":"10.1109\/TMM.2022.3152390"},{"issue":"8","key":"9478_CR24","doi-asserted-by":"publisher","first-page":"2012","DOI":"10.1109\/TMM.2019.2951461","volume":"22","author":"H Zhang","year":"2019","unstructured":"Zhang H, Xu X, He H, He S, Han G, Qin J, Wu D (2019) Fast user-guided single image reflection removal via edge-aware cascaded networks. IEEE Trans Multimedia 22(8):2012\u20132023","journal-title":"IEEE Trans Multimedia"},{"key":"9478_CR25","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser \u0141, Polosukhin I (2017) Attention is all you need. Adv Neural Inf Process Syst 30"},{"key":"9478_CR26","unstructured":"Ji H, Feng X, Pei W, Li J, Lu G (2021) U2-former: A nested u-shaped transformer for image restoration. arXiv preprint arXiv:2112.02279"},{"key":"9478_CR27","unstructured":"Goodfellow IJ, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2014) Generative adversarial nets. In: Proceedings of the 27th international conference on neural information processing systems, pp 2672\u20132680"},{"issue":"9","key":"9478_CR28","doi-asserted-by":"publisher","first-page":"7209","DOI":"10.1007\/s00521-021-06841-7","volume":"34","author":"J Xiao","year":"2022","unstructured":"Xiao J, Zhang S, Yao Y, Wang Z, Zhang Y, Wang Y-F (2022) Generative adversarial network with hybrid attention and compromised normalization for multi-scene image conversion. Neural Comput Appl 34(9):7209\u20137225","journal-title":"Neural Comput Appl"},{"key":"9478_CR29","doi-asserted-by":"crossref","unstructured":"Huang G, Jafari AH (2021) Enhanced balancing gan: minority-class image generation. Neural Comput Appl:1\u201310","DOI":"10.1007\/s00521-021-06163-8"},{"key":"9478_CR30","doi-asserted-by":"crossref","unstructured":"Ma D, Wan R, Shi B, Kot AC, Duan L-Y (2019) Learning to jointly generate and separate reflections. In: Proceedings of the IEEE international conference on computer vision, pp 2444\u20132452","DOI":"10.1109\/ICCV.2019.00253"},{"key":"9478_CR31","doi-asserted-by":"crossref","unstructured":"Zhang L, Lu Y, Li J, Chen F, Lu G, Zhang D (2023) Deep adaptive hiding network for image hiding using attentive frequency extraction and gradual depth extraction. Neural Comput Appl:1\u201319","DOI":"10.1007\/s00521-023-08274-w"},{"key":"9478_CR32","doi-asserted-by":"publisher","first-page":"3782","DOI":"10.1109\/TMM.2021.3107688","volume":"24","author":"Z Wu","year":"2021","unstructured":"Wu Z, Zhuang C, Shi J, Guo J, Xiao J, Zhang X, Yan D-M (2021) Single-image specular highlight removal via real-world dataset construction. IEEE Trans Multimedia 24:3782\u20133793","journal-title":"IEEE Trans Multimedia"},{"key":"9478_CR33","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"9478_CR34","unstructured":"Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556"},{"key":"9478_CR35","doi-asserted-by":"crossref","unstructured":"Gatys L, Ecker AS, Bethge M (2015) Texture synthesis using convolutional neural networks. Adv Neural Inf Process Syst 28","DOI":"10.1109\/CVPR.2016.265"},{"key":"9478_CR36","doi-asserted-by":"crossref","unstructured":"Hui Z, Gao X, Yang Y, Wang X (2019) Lightweight image super-resolution with information multi-distillation network. In: Proceedings of the 27th Acm international conference on multimedia, pp 2024\u20132032","DOI":"10.1145\/3343031.3351084"},{"key":"9478_CR37","doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7132\u20137141","DOI":"10.1109\/CVPR.2018.00745"},{"key":"9478_CR38","doi-asserted-by":"crossref","unstructured":"Huang G, Liu Z, Van Der\u00a0Maaten L, Weinberger KQ (2017) Densely connected convolutional networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4700\u20134708","DOI":"10.1109\/CVPR.2017.243"},{"key":"9478_CR39","doi-asserted-by":"crossref","unstructured":"Johnson J, Alahi A, Fei-Fei L (2016) Perceptual losses for real-time style transfer and super-resolution. In: European conference on computer vision. Springer, pp 694\u2013711","DOI":"10.1007\/978-3-319-46475-6_43"},{"key":"9478_CR40","unstructured":"Jolicoeur-Martineau A (2018) The relativistic discriminator: a key element missing from standard gan. arXiv preprint arXiv:1807.00734"},{"key":"9478_CR41","doi-asserted-by":"crossref","unstructured":"Isola P, Zhu J-Y, Zhou T, Efros AA (2017) Image-to-image translation with conditional adversarial networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1125\u20131134","DOI":"10.1109\/CVPR.2017.632"},{"key":"9478_CR42","first-page":"24683","volume":"34","author":"Q Hu","year":"2021","unstructured":"Hu Q, Guo X (2021) Trash or treasure? an interactive dual-stream strategy for single image reflection separation. Adv Neural Inf Process Syst 34:24683\u201324694","journal-title":"Adv Neural Inf Process Syst"},{"key":"9478_CR43","unstructured":"Kingma DP, Ba J (2014) Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"key":"9478_CR44","doi-asserted-by":"crossref","unstructured":"Wan R, Shi B, Duan L-Y, Tan A-H, Kot AC (2017) Benchmarking single-image reflection removal algorithms. In: Proceedings of the IEEE international conference on computer vision, pp 3922\u20133930","DOI":"10.1109\/ICCV.2017.423"},{"key":"9478_CR45","doi-asserted-by":"crossref","unstructured":"Dong Z, Xu K, Yang Y, Bao H, Xu W, Lau RW (2021) Location-aware single image reflection removal. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 5017\u20135026","DOI":"10.1109\/ICCV48922.2021.00497"},{"key":"9478_CR46","doi-asserted-by":"crossref","unstructured":"Zhang Y-N, Shen L, Li Q (2022) Content and gradient model-driven deep network for single image reflection removal. In: Proceedings of the 30th ACM international conference on multimedia, pp 6802\u20136812","DOI":"10.1145\/3503161.3547918"},{"key":"9478_CR47","doi-asserted-by":"crossref","unstructured":"Das P, Karaoglu S, Gevers T (2022) Pie-net: Photometric invariant edge guided network for intrinsic image decomposition. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 19790\u201319799","DOI":"10.1109\/CVPR52688.2022.01917"},{"key":"9478_CR48","doi-asserted-by":"crossref","unstructured":"Butler DJ, Wulff J, Stanley GB, Black MJ (2012) A naturalistic open source movie for optical flow evaluation. In: Computer Vision\u2013ECCV 2012: 12th European conference on computer vision, Florence, Italy, October 7-13, 2012, Proceedings, Part VI 12. Springer, pp 611\u2013625","DOI":"10.1007\/978-3-642-33783-3_44"},{"key":"9478_CR49","unstructured":"Chang AX, Funkhouser T, Guibas L, Hanrahan P, Huang Q, Li Z, Savarese S, Savva M, Song S, Su H, et al (2015) Shapenet: An information-rich 3d model repository. arXiv preprint arXiv:1512.03012"},{"key":"9478_CR50","doi-asserted-by":"crossref","unstructured":"Grosse R, Johnson MK, Adelson EH, Freeman WT (2009) Ground truth dataset and baseline evaluations for intrinsic image algorithms. In: 2009 IEEE 12th international conference on computer vision, pp 2335\u20132342 . IEEE","DOI":"10.1109\/ICCV.2009.5459428"},{"key":"9478_CR51","doi-asserted-by":"crossref","unstructured":"Grosse R, Johnson MK, Adelson EH, Freeman WT (2009) Ground truth dataset and baseline evaluations for intrinsic image algorithms. In: 2009 IEEE 12th international conference on computer vision, pp 2335\u20132342 . IEEE","DOI":"10.1109\/ICCV.2009.5459428"},{"issue":"8","key":"9478_CR52","doi-asserted-by":"publisher","first-page":"1670","DOI":"10.1109\/TPAMI.2014.2377712","volume":"37","author":"JT Barron","year":"2014","unstructured":"Barron JT, Malik J (2014) Shape, illumination, and reflectance from shading. IEEE Trans Pattern Anal Mach Intell 37(8):1670\u20131687","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9478_CR53","doi-asserted-by":"crossref","unstructured":"Li Z, Snavely N (2018) Learning intrinsic image decomposition from watching the world. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 9039\u20139048","DOI":"10.1109\/CVPR.2018.00942"},{"key":"9478_CR54","doi-asserted-by":"crossref","unstructured":"Liu Y, Li Y, You S, Lu F (2020) Unsupervised learning for intrinsic image decomposition from a single image. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 3248\u20133257","DOI":"10.1109\/CVPR42600.2020.00331"},{"key":"9478_CR55","doi-asserted-by":"crossref","unstructured":"Li Y, Brown MS (2014) Single image layer separation using relative smoothness. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2752\u20132759","DOI":"10.1109\/CVPR.2014.346"},{"key":"9478_CR56","doi-asserted-by":"crossref","unstructured":"Ma W-C, Chu H, Zhou B, Urtasun R, Torralba A (2018) Single image intrinsic decomposition without a single intrinsic image. In: Proceedings of the European conference on computer vision (ECCV), pp 201\u2013217","DOI":"10.1007\/978-3-030-01264-9_13"},{"key":"9478_CR57","doi-asserted-by":"crossref","unstructured":"Liu Y, Lu F (2020) Separate in latent space: Unsupervised single image layer separation. In: Proceedings of the AAAI conference on artificial intelligence, vol 34, pp 11661\u201311668","DOI":"10.1609\/aaai.v34i07.6835"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09478-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-09478-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-09478-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,13]],"date-time":"2024-04-13T20:18:27Z","timestamp":1713039507000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-09478-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,27]]},"references-count":57,"journal-issue":{"issue":"14","published-print":{"date-parts":[[2024,5]]}},"alternative-id":["9478"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-09478-4","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,27]]},"assertion":[{"value":"2 March 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 January 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 February 2024","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 have no relevant financial or non-financial interests to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}