{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,6]],"date-time":"2025-12-06T17:18:41Z","timestamp":1765041521716,"version":"3.38.0"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Hasso-Plattner-Institut f\u00fcr Digital Engineering gGmbH"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2025,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>While methods for generative image synthesis and example-based stylization produce impressive results, their black-box style representation intertwines shape, texture, and color aspects, limiting precise stylistic control and editing of artistic images. We introduce a novel method for decomposing the style of an artistic image that enables interactive geometric shape abstraction and texture control. We spatially decompose the input image into geometric shapes and an overlaying parametric texture representation, facilitating independent manipulation of color and texture. The parameters in this texture representation, comprising the image\u2019s high-frequency details, control painterly attributes in a series of differentiable stylization filters. Shape decomposition is achieved using either segmentation or stroke-based neural rendering techniques. We demonstrate that our shape and texture decoupling enables diverse stylistic edits, including adjustments in shape, stroke, and painterly attributes such as contours and surface relief. Moreover, we demonstrate shape and texture style transfer in the parametric space using both reference images and text prompts and accelerate these by training networks for single- and arbitrary-style parameter prediction.<\/jats:p>","DOI":"10.1007\/s00371-024-03521-0","type":"journal-article","created":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T23:04:01Z","timestamp":1719875041000},"page":"2107-2122","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Artistic style decomposition for texture and shape editing"],"prefix":"10.1007","volume":"41","author":[{"given":"Max","family":"Reimann","sequence":"first","affiliation":[]},{"given":"Martin","family":"B\u00fc\u00dfemeyer","sequence":"additional","affiliation":[]},{"given":"Benito","family":"Buchheim","sequence":"additional","affiliation":[]},{"given":"Amir","family":"Semmo","sequence":"additional","affiliation":[]},{"given":"J\u00fcrgen","family":"D\u00f6llner","sequence":"additional","affiliation":[]},{"given":"Matthias","family":"Trapp","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,1]]},"reference":[{"unstructured":"Hertzmann, A.: Toward modeling creative processes for algorithmic painting. arXiv preprint arXiv:2205.01605 (2022)","key":"3521_CR1"},{"doi-asserted-by":"publisher","unstructured":"Winnem\u00f6ller, H.: NPR in the wild. In: Image and Video-Based Artistic Stylisation, pp. 353\u2013374 (2012). https:\/\/doi.org\/10.1007\/978-1-4471-4519-6","key":"3521_CR2","DOI":"10.1007\/978-1-4471-4519-6"},{"doi-asserted-by":"publisher","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proc. CVPR, pp. 10684\u201310695 (2022). https:\/\/doi.org\/10.1109\/cvpr52688.2022.01042","key":"3521_CR3","DOI":"10.1109\/cvpr52688.2022.01042"},{"doi-asserted-by":"publisher","unstructured":"Gatys, L.A., Ecker, A.S., Bethge, M.: Image style transfer using convolutional neural networks. In: Proc. CVPR, pp. 2414\u20132423 (2016). https:\/\/doi.org\/10.1109\/cvpr.2016.265","key":"3521_CR4","DOI":"10.1109\/cvpr.2016.265"},{"doi-asserted-by":"publisher","unstructured":"Huang, X., Belongie, S.: Arbitrary style transfer in real-time with adaptive instance normalization. In: Proc. ICCV, pp. 1501\u20131510 (2017). https:\/\/doi.org\/10.1109\/iccv.2017.167","key":"3521_CR5","DOI":"10.1109\/iccv.2017.167"},{"issue":"11","key":"3521_CR6","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/tpami.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., S\u00fcsstrunk, S.: SLIC superpixels compared to state-of-the-art superpixel methods. IEEE TPAMI 34(11), 2274\u20132282 (2012). https:\/\/doi.org\/10.1109\/tpami.2012.120","journal-title":"IEEE TPAMI"},{"doi-asserted-by":"publisher","unstructured":"Liu, S., Lin, T., He, D., Li, F., Deng, R., Li, X., Ding, E., Wang, H.: Paint transformer: Feed forward neural painting with stroke prediction. In: Proc. ICCV, pp. 6598\u20136607 (2021). https:\/\/doi.org\/10.1109\/iccv48922.2021.00653","key":"3521_CR7","DOI":"10.1109\/iccv48922.2021.00653"},{"doi-asserted-by":"publisher","unstructured":"Zou, Z., Shi, T., Qiu, S., Yuan, Y., Shi, Z.: Stylized neural painting. In: Proc. CVPR, pp. 15689\u201315698 (2021). https:\/\/doi.org\/10.1109\/cvpr46437.2021.01543","key":"3521_CR8","DOI":"10.1109\/cvpr46437.2021.01543"},{"issue":"5","key":"3521_CR9","doi-asserted-by":"publisher","first-page":"866","DOI":"10.1109\/TVCG.2012.160","volume":"19","author":"JE Kyprianidis","year":"2012","unstructured":"Kyprianidis, J.E., Collomosse, J., Wang, T., Isenberg, T.: State of the \u201cart\u2019\u2019: a taxonomy of artistic stylization techniques for images and video. IEEE TVCG 19(5), 866\u2013885 (2012). https:\/\/doi.org\/10.1109\/TVCG.2012.160","journal-title":"IEEE TVCG"},{"doi-asserted-by":"publisher","unstructured":"L\u00f6tzsch, W., Reimann, M., B\u00fcssemeyer, M., Semmo, A., D\u00f6llner, J., Trapp, M.: WISE: Whitebox image stylization by example-based learning. In: Proc. ECCV, pp. 135\u2013152 (2022). https:\/\/doi.org\/10.1007\/978-3-031-19790-1_9","key":"3521_CR10","DOI":"10.1007\/978-3-031-19790-1_9"},{"doi-asserted-by":"publisher","unstructured":"Kolkin, N., Salavon, J., Shakhnarovich, G.: Style transfer by relaxed optimal transport and self-similarity. In: Proc. CVPR (2019).https:\/\/doi.org\/10.1109\/cvpr.2019.01029","key":"3521_CR11","DOI":"10.1109\/cvpr.2019.01029"},{"doi-asserted-by":"publisher","unstructured":"Kwon, G., Ye, J.C.: CLIPstyler: Image style transfer with a single text condition. In: Proc. CVPR, pp. 18062\u201318071 (2022). https:\/\/doi.org\/10.1109\/cvpr52688.2022.01753","key":"3521_CR12","DOI":"10.1109\/cvpr52688.2022.01753"},{"doi-asserted-by":"publisher","unstructured":"B\u00fc\u00dfemeyer, M., Reimann, M., Buchheim, B., Semmo, A., D\u00f6llner, J., Trapp, M.: Controlling geometric abstraction and texture for artistic images. In: Proc. IEEE International Conference on Cyberworlds (CW), pp. 1\u20138 (2023). https:\/\/doi.org\/10.1109\/cw58918.2023.00011","key":"3521_CR13","DOI":"10.1109\/cw58918.2023.00011"},{"doi-asserted-by":"publisher","unstructured":"Gatys, L.A., Ecker, A.S., Bethge, M., Hertzmann, A., Shechtman, E.: Controlling perceptual factors in neural style transfer. In: Proc. CVPR, pp. 3730\u20133738 (2017). https:\/\/doi.org\/10.1109\/cvpr.2017.397","key":"3521_CR14","DOI":"10.1109\/cvpr.2017.397"},{"doi-asserted-by":"publisher","unstructured":"Reimann, M., Buchheim, B., Semmo, A., D\u00f6llner, J., Trapp, M.: Controlling strokes in fast neural style transfer using content transforms. The Visual Computer, 1\u201315 (2022) https:\/\/doi.org\/10.1007\/s00371-022-02518-x","key":"3521_CR15","DOI":"10.1007\/s00371-022-02518-x"},{"doi-asserted-by":"publisher","unstructured":"Jing, Y., Liu, Y., Yang, Y., Feng, Z., Yu, Y., Tao, D., Song, M.: Stroke controllable fast style transfer with adaptive receptive fields. In: Proc. ECCV (2018). https:\/\/doi.org\/10.1007\/978-3-030-01261-8_15","key":"3521_CR16","DOI":"10.1007\/978-3-030-01261-8_15"},{"unstructured":"Radford, A., Kim, J.W., et\u00a0al.: Learning transferable visual models from natural language supervision. In: Proc. ICML, pp. 8748\u20138763 (2021)","key":"3521_CR17"},{"unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. In: Proc. NIPS (2014)","key":"3521_CR18"},{"doi-asserted-by":"publisher","unstructured":"Karras, T., Laine, S., Aila, T.: A style-based generator architecture for generative adversarial networks. In: Proc. CVPR, pp. 4401\u20134410 (2019).https:\/\/doi.org\/10.1109\/cvpr.2019.00453","key":"3521_CR19","DOI":"10.1109\/cvpr.2019.00453"},{"unstructured":"Dhariwal, P., Nichol, A.: Diffusion models beat gans on image synthesis. In: Proc. NIPS, vol. 34, pp. 8780\u20138794 (2021)","key":"3521_CR20"},{"doi-asserted-by":"crossref","unstructured":"Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E., Ghasemipour, S.K.S., Ayan, B.K., Mahdavi, S.S., Lopes, R.G., et al.: Photorealistic text-to-image diffusion models with deep language understanding. arXiv preprint arXiv:2205.11487 (2022)","key":"3521_CR21","DOI":"10.1145\/3528233.3530757"},{"doi-asserted-by":"publisher","unstructured":"Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., Aila, T.: Analyzing and improving the image quality of StyleGAN. In: Proc. CVPR, pp. 8110\u20138119 (2020). https:\/\/doi.org\/10.1109\/cvpr42600.2020.00813","key":"3521_CR22","DOI":"10.1109\/cvpr42600.2020.00813"},{"issue":"4","key":"3521_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3450626.3459860","volume":"40","author":"W Jang","year":"2021","unstructured":"Jang, W., Ju, G., Jung, Y., Yang, J., Tong, X., Lee, S.: Stylecarigan: caricature generation via stylegan feature map modulation. ACM TOG 40(4), 1\u201316 (2021). https:\/\/doi.org\/10.1145\/3450626.3459860","journal-title":"ACM TOG"},{"doi-asserted-by":"publisher","unstructured":"Chong, M.J., Forsyth, D.: Jojogan: One shot face stylization. In: European Conference on Computer Vision, pp. 128\u2013152 (2022). https:\/\/doi.org\/10.1007\/978-3-031-19787-1_8","key":"3521_CR24","DOI":"10.1007\/978-3-031-19787-1_8"},{"doi-asserted-by":"publisher","unstructured":"Singh, J., Zheng, L., Smith, C., Echevarria, J.: Paint2pix: interactive painting based progressive image synthesis and editing. In: Proc. ECCV, pp. 678\u2013695 (2022).https:\/\/doi.org\/10.1007\/978-3-031-19781-9_39","key":"3521_CR25","DOI":"10.1007\/978-3-031-19781-9_39"},{"doi-asserted-by":"crossref","unstructured":"Patashnik, O., Wu, Z., Shechtman, E., Cohen-Or, D., Lischinski, D.: StyleCLIP: Text-driven manipulation of stylegan imagery. In: Proc. ICCV, pp. 2085\u20132094 (2021)","key":"3521_CR26","DOI":"10.1109\/ICCV48922.2021.00209"},{"issue":"4","key":"3521_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/iccv48922.2021.00209","volume":"41","author":"R Gal","year":"2022","unstructured":"Gal, R., Patashnik, O., Maron, H., Bermano, A.H., Chechik, G., Cohen-Or, D.: Stylegan-nada: Clip-guided domain adaptation of image generators. ACM TOG 41(4), 1\u201313 (2022). https:\/\/doi.org\/10.1109\/iccv48922.2021.00209","journal-title":"ACM TOG"},{"doi-asserted-by":"publisher","unstructured":"Richardson, E., Alaluf, Y., Patashnik, O., Nitzan, Y., Azar, Y., Shapiro, S., Cohen-Or, D.: Encoding in style: a stylegan encoder for image-to-image translation. In: Proc. CVPR, pp. 2287\u20132296 (2021). https:\/\/doi.org\/10.1109\/cvpr46437.2021.00232","key":"3521_CR28","DOI":"10.1109\/cvpr46437.2021.00232"},{"unstructured":"Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., Ganguli, S.: Deep unsupervised learning using nonequilibrium thermodynamics. In: Proc. ICML, pp. 2256\u20132265 (2015)","key":"3521_CR29"},{"doi-asserted-by":"publisher","unstructured":"Kim, G., Kwon, T., Ye, J.C.: Diffusionclip: Text-guided diffusion models for robust image manipulation. In: Proc. CVPR, pp. 2426\u20132435 (2022). https:\/\/doi.org\/10.1109\/cvpr52688.2022.00246","key":"3521_CR30","DOI":"10.1109\/cvpr52688.2022.00246"},{"doi-asserted-by":"publisher","unstructured":"Kawar, B., Zada, S., Lang, O., Tov, O., Chang, H., Dekel, T., Mosseri, I., Irani, M.: Imagic: Text-based real image editing with diffusion models. arXiv preprint arXiv:2210.09276 (2022) https:\/\/doi.org\/10.48550\/arxiv.2205.11487","key":"3521_CR31","DOI":"10.48550\/arxiv.2205.11487"},{"doi-asserted-by":"crossref","unstructured":"Chung, J., Hyun, S., Heo, J.-P.: Style injection in diffusion: A training-free approach for adapting large-scale diffusion models for style transfer. arXiv preprint arXiv:2312.09008 (2023)","key":"3521_CR32","DOI":"10.1109\/CVPR52733.2024.00840"},{"issue":"3","key":"3521_CR33","doi-asserted-by":"publisher","first-page":"1221","DOI":"10.1145\/1179352.1142018","volume":"25","author":"H Winnem\u00f6ller","year":"2006","unstructured":"Winnem\u00f6ller, H., Olsen, S.C., Gooch, B.: Real-time video abstraction. ACM TOG 25(3), 1221\u20131226 (2006). https:\/\/doi.org\/10.1145\/1179352.1142018","journal-title":"Real-time video abstraction. ACM TOG"},{"doi-asserted-by":"publisher","unstructured":"Semmo, A., Limberger, D., Kyprianidis, J.E., D\u00f6llner, J.: Image stylization by interactive oil paint filtering. Computers & Graphics 55, 157\u2013171 (2016) https:\/\/doi.org\/10.1016\/j.cag.2015.12.001","key":"3521_CR34","DOI":"10.1016\/j.cag.2015.12.001"},{"doi-asserted-by":"publisher","unstructured":"Bousseau, A., Kaplan, M., Thollot, J., Sillion, F.X.: Interactive watercolor rendering with temporal coherence and abstraction. In: Proc. NPAR, pp. 141\u2013149 (2006). https:\/\/doi.org\/10.1145\/1124728.1124751","key":"3521_CR35","DOI":"10.1145\/1124728.1124751"},{"doi-asserted-by":"publisher","unstructured":"Song, Y.-Z., Rosin, P.L., Hall, P.M., Collomosse, J.P.: Arty shapes. In: CAe, pp. 65\u201372 (2008). https:\/\/doi.org\/10.2312\/compaesth\/compaesth08\/065-072","key":"3521_CR36","DOI":"10.2312\/compaesth\/compaesth08\/065-072"},{"doi-asserted-by":"crossref","unstructured":"Ihde, L., Semmo, A., D\u00f6llner, J., Trapp, M.: Design space of geometry-based image abstraction techniques with vectorization applications. Journal of WSCG, 99\u2013108 (2022)","key":"3521_CR37","DOI":"10.24132\/JWSCG.2022.12"},{"doi-asserted-by":"publisher","unstructured":"Hertzmann, A.: Painterly rendering with curved brush strokes of multiple sizes. In: Proc. SIGGRAPH, pp. 453\u2013460 (1998). https:\/\/doi.org\/10.1145\/280814.280951","key":"3521_CR38","DOI":"10.1145\/280814.280951"},{"doi-asserted-by":"publisher","unstructured":"Huang, Z., Heng, W., Zhou, S.: Learning to paint with model-based deep reinforcement learning. In: Proc. ICCV, pp. 8709\u20138718 (2019). https:\/\/doi.org\/10.1109\/iccv.2019.00880","key":"3521_CR39","DOI":"10.1109\/iccv.2019.00880"},{"issue":"6","key":"3521_CR40","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1016\/j.cag.2012.03.004","volume":"36","author":"H Winnem\u00f6ller","year":"2012","unstructured":"Winnem\u00f6ller, H., Kyprianidis, J.E., Olsen, S.C.: XDoG: Advanced Image Stylization with eXtended Difference-of-Gaussians. Computers & Graphics 36(6), 740\u2013753 (2012)","journal-title":"Computers & Graphics"},{"issue":"6","key":"3521_CR41","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1145\/360825.360839","volume":"18","author":"BT Phong","year":"1975","unstructured":"Phong, B.T.: Illumination for computer generated pictures. Commun. ACM 18(6), 311\u2013317 (1975). https:\/\/doi.org\/10.1145\/360825.360839","journal-title":"Commun. ACM"},{"issue":"10","key":"3521_CR42","first-page":"1451","volume":"20","author":"M Wang","year":"2014","unstructured":"Wang, M., Wang, B., Fei, Y., Qian, K., Wang, W., Chen, J., Yong, J.-H.: Towards photo watercolorizatin with artistic verisimilitude. IEEE TVCG 20(10), 1451\u20131460 (2014)","journal-title":"IEEE TVCG"},{"unstructured":"Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. In: Proc. ICLR (2015)","key":"3521_CR43"},{"doi-asserted-by":"publisher","unstructured":"Johnson, J., Alahi, A., Fei-Fei, L.: Perceptual losses for real-time style transfer and super-resolution. In: Proc. ECCV (2016). https:\/\/doi.org\/10.1007\/978-3-319-46475-6_43","key":"3521_CR44","DOI":"10.1007\/978-3-319-46475-6_43"},{"doi-asserted-by":"publisher","unstructured":"Park, D.Y., Lee, K.H.: Arbitrary style transfer with style-attentional networks. In: Proc. CVPR, pp. 5880\u20135888 (2019).https:\/\/doi.org\/10.1109\/cvpr.2019.00603","key":"3521_CR45","DOI":"10.1109\/cvpr.2019.00603"},{"unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: Proc. ICLR (2015)","key":"3521_CR46"},{"doi-asserted-by":"publisher","unstructured":"Lin, T., et al.: Microsoft COCO: common objects in context. CoRR (2014). arxiv:1405.0312 (or) https:\/\/doi.org\/10.1007\/978-3-319-10602-1_48","key":"3521_CR47","DOI":"10.1007\/978-3-319-10602-1_48"},{"unstructured":"Nichol, K.: Kaggle Painter by Numbers (WikiArt) (2016). https:\/\/www.kaggle.com\/c\/painter-by-numbers","key":"3521_CR48"},{"doi-asserted-by":"publisher","unstructured":"Ranftl, R., Bochkovskiy, A., Koltun, V.: Vision transformers for dense prediction. In: Proc. ICCV, pp. 12179\u201312188 (2021).https:\/\/doi.org\/10.1109\/iccv48922.2021.01196","key":"3521_CR49","DOI":"10.1109\/iccv48922.2021.01196"},{"unstructured":"Jonschkowski, R., Brock, O.: End-to-end learnable histogram filters (2016)","key":"3521_CR50"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03521-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-024-03521-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03521-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,3]],"date-time":"2025-03-03T11:31:24Z","timestamp":1741001484000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-024-03521-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,1]]},"references-count":50,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,3]]}},"alternative-id":["3521"],"URL":"https:\/\/doi.org\/10.1007\/s00371-024-03521-0","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"type":"print","value":"0178-2789"},{"type":"electronic","value":"1432-2315"}],"subject":[],"published":{"date-parts":[[2024,7,1]]},"assertion":[{"value":"27 May 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 July 2024","order":2,"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 no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}