Realistic text replacement with non-uniform style conditioning

7 Jun 2020 · Arseny Nerinovsky, Igor Buzhinsky, Andey Filchencov ·

In this work, we study the possibility of realistic text replacement, the goal of which is to replace text present in the image with user-supplied text. The replacement should be performed in a way that will not allow distinguishing the resulting image from the original one. We achieve this goal by developing a novel non-uniform style conditioning layer and apply it to an encoder-decoder ResNet based architecture. The resulting model is a single-stage model, with no post-processing. The proposed model achieves realistic text replacement and outperforms existing approaches on ICDAR MLT.

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1x1 Convolution • Average Pooling • Batch Normalization • Bottleneck Residual Block • Convolution • Global Average Pooling • Kaiming Initialization • Max Pooling • ReLU • Residual Block • Residual Connection • ResNet

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Realistic text replacement with non-uniform style conditioning

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