{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T02:13:09Z","timestamp":1784686389959,"version":"3.55.0"},"reference-count":31,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2018,7,30]],"date-time":"2018-07-30T00:00:00Z","timestamp":1532908800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Graph."],"published-print":{"date-parts":[[2018,8,31]]},"abstract":"<jats:p>The real world exhibits an abundance of non-stationary textures. Examples include textures with large scale structures, as well as spatially variant and inhomogeneous textures. While existing example-based texture synthesis methods can cope well with stationary textures, non-stationary textures still pose a considerable challenge, which remains unresolved. In this paper, we propose a new approach for example-based non-stationary texture synthesis. Our approach uses a generative adversarial network (GAN), trained to double the spatial extent of texture blocks extracted from a specific texture exemplar. Once trained, the fully convolutional generator is able to expand the size of the entire exemplar, as well as of any of its sub-blocks. We demonstrate that this conceptually simple approach is highly effective for capturing large scale structures, as well as other non-stationary attributes of the input exemplar. As a result, it can cope with challenging textures, which, to our knowledge, no other existing method can handle.<\/jats:p>","DOI":"10.1145\/3197517.3201285","type":"journal-article","created":{"date-parts":[[2018,7,31]],"date-time":"2018-07-31T15:56:23Z","timestamp":1533052583000},"page":"1-13","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":134,"title":["Non-stationary texture synthesis by adversarial expansion"],"prefix":"10.1145","volume":"37","author":[{"given":"Yang","family":"Zhou","sequence":"first","affiliation":[{"name":"Shenzhen University and Huazhong University of Science &amp; Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Zhu","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang","family":"Bai","sequence":"additional","affiliation":[{"name":"Huazhong University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dani","family":"Lischinski","sequence":"additional","affiliation":[{"name":"The Hebrew University of Jerusalem"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Cohen-Or","sequence":"additional","affiliation":[{"name":"Shenzhen University and Tel Aviv University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Huang","sequence":"additional","affiliation":[{"name":"Shenzhen University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2018,7,30]]},"reference":[{"key":"e_1_2_2_1_1","volume-title":"Learning Texture Manifolds with the Periodic Spatial GAN. 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Texture Synthesis Using Convolutional Neural Networks. Advances in Neural Information Processing Systems 28 (May 2015) 262--270. http:\/\/arxiv.org\/abs\/1505.07376   L.A. Gatys A.S. Ecker and M. Bethge. 2015a. Texture Synthesis Using Convolutional Neural Networks. Advances in Neural Information Processing Systems 28 (May 2015) 262--270. http:\/\/arxiv.org\/abs\/1505.07376"},{"key":"e_1_2_2_6_1","volume-title":"A Neural Algorithm of Artistic Style. CoRR abs\/1508.06576 (Aug","author":"Gatys Leon A.","year":"2015","unstructured":"Leon A. Gatys , Alexander S. Ecker , and Matthias Bethge . 2015b. A Neural Algorithm of Artistic Style. CoRR abs\/1508.06576 (Aug 2015 ). http:\/\/arxiv.org\/abs\/1508.06576 Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge. 2015b. A Neural Algorithm of Artistic Style. CoRR abs\/1508.06576 (Aug 2015). http:\/\/arxiv.org\/abs\/1508.06576"},{"key":"e_1_2_2_7_1","volume-title":"Generative Adversarial Networks. 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