Realistic Text Replacement With Non-Uniform Style Conditioning

نویسندگان

چکیده

In this work, we study the possibility of realistic text replacement. The goal replacement is to replace present in image with user-supplied text. should be performed a way that will not allow distinguishing resulting from original one. We achieve by developing novel non-uniform style conditioning layer and apply it an encoder-decoder ResNet based architecture. model single-stage model, no post-processing. train combination adversarial, style, content $L_{1}$ losses. Qualitative quantitative evaluations show achieves outperforms existing approaches multilingual challenging scenarios. Quantitative evaluation direct metrics, like SSIM PSNR, proxy metrics on performance recognition model. proposed has several potential applications augmented reality.

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2021

ISSN: ['2169-3536']

DOI: https://doi.org/10.1109/access.2021.3071666