Journal of Beijing Normal University, Volume. 61, Issue 3, 285(2025)
Uncertainty-awared generative network for Chinese scene text editing
A Chinese scene text editing (CSTE) method, based on research but incorporating uncertainty modeling and identifying effective technical solution, is proposed in this work. This new method optimizes prediction noise through an uncertainty-guided adjustment mechanism, improving the accuracy of noise estimation, thereby enhancing the clarity and structural integrity of the generated text. Additionally, by filtering irrelevant information from both textual and visual features, the method improves cross-modal alignment capabilities, achieving a seamless fusion of text and background textures.
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GAO Yutong, ZHANG Ying, LIU Xianggan, LIU Yidian, JIANG Shan, GUO Ziyi, SONG Feifan. Uncertainty-awared generative network for Chinese scene text editing[J]. Journal of Beijing Normal University, 2025, 61(3): 285
Received: Apr. 9, 2025
Accepted: Aug. 21, 2025
Published Online: Aug. 21, 2025
The Author Email: LIU Xianggan (liuxg@hust.edu.cn)