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- W2995942257 abstract "A precise, controllable, interpretable and easily trainable text removal approach is necessary for both user-specific and large-scale text removal applications. To achieve this, we propose a one-stage mask-based text inpainting network, MTRNet++. It has a novel architecture that includes mask-refine, coarse-inpainting and fine-inpainting branches, and attention blocks. With this architecture, MTRNet++ can remove text either with or without an external mask. It achieves state-of-the-art results on both the Oxford and SCUT datasets without using external ground-truth masks. The results of ablation studies demonstrate that the proposed multi-branch architecture with attention blocks is effective and essential. It also demonstrates controllability and interpretability." @default.
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- W2995942257 date "2020-12-01" @default.
- W2995942257 modified "2023-10-16" @default.
- W2995942257 title "MTRNet++: One-stage mask-based scene text eraser" @default.
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- W2995942257 doi "https://doi.org/10.1016/j.cviu.2020.103066" @default.
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