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Driven by deep learning and large\u2010scale generative models, the field has transitioned from low\u2010level texture synthesis to high\u2010level semantic generation, yielding major breakthroughs in structural fidelity and visual realism. Centring on the generative paradigm as the architectural trajectory, this survey systematically categorizes the 30\u2010year evolution of image inpainting into three distinct technological generations: traditional prior\u2010driven synthesis, deep learning data\u2010driven reconstruction and modern foundation model\u2010driven generation. Despite this progress, highly competitive methods still struggle with large\u2010scale missing regions, global consistency in complex scenes, fine\u2010grained micro\u2010details and alignment with human visual perception. To address these gaps, we critically evaluate the technical paradigms and main bottlenecks within each of these evolutionary stages. We categorize and compare mainstream breakthroughs across high\u2010resolution restoration, text\u2010guided synthesis and complex scene generation. Furthermore, we compile standard benchmarks, evaluation metrics and quantitative performance comparisons of representative algorithms. Finally, we dissect open challenges\u2014focusing on cross\u2010scene generalization and evaluation metric alignment\u2014and outline future trajectories, particularly the integration of inpainting with text\u2010guided foundation models, providing a definitive reference for future theoretical and engineering advancements.<\/jats:p>","DOI":"10.1111\/exsy.70386","type":"journal-article","created":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T23:01:12Z","timestamp":1785798072000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Image Inpainting in 30\u2009Years: A Survey"],"prefix":"10.1111","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7204-3654","authenticated-orcid":false,"given":"Zhenhua","family":"Yu","sequence":"first","affiliation":[{"name":"College of Artificial Intelligence and Computer Science Xi'an University of Science and Technology  Xi'an China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4020-5205","authenticated-orcid":false,"given":"Hengxiang","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence and Computer Science Xi'an University of Science and Technology  Xi'an China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6441-4232","authenticated-orcid":false,"given":"Wenchao","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence and Computer Science Xi'an University of Science and Technology  Xi'an China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2767-3999","authenticated-orcid":false,"given":"Wei","family":"Song","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering Northeastern University  Shenyang China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5816-4126","authenticated-orcid":false,"given":"Yu","family":"Zheng","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computer Science University of California, Irvine  Irvine California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2517-2867","authenticated-orcid":false,"given":"Michele","family":"Nappi","sequence":"additional","affiliation":[{"name":"Department of Computer Science University of Salerno  Fisciano Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4745-8361","authenticated-orcid":false,"given":"Junxin","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Software Dalian University of Technology  Dalian China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,3]]},"reference":[{"key":"e_1_2_9_2_1","unstructured":"Agarwal S. 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