TextWand unifies scene text removal, generation and replacement via rendering/erasure decomposition, ORPE for layout fidelity, RAS for clean erasure, and the new TextWand-Bench dataset, claiming superior accuracy and quality over prior models.
Improving diffusion models for scene text editing with dual encoders
3 Pith papers cite this work. Polarity classification is still indexing.
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POCA combines Pareto optimization with curriculum alignment to improve multi-reward reinforcement learning for visual text generation without relying on weighted sums.
SkyReels-Text enables simultaneous fine-grained editing of multiple text regions in posters using arbitrary glyph patches for font control without labels or test-time fine-tuning.
citing papers explorer
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TextWand: A Unified Framework for Scene Text Editing
TextWand unifies scene text removal, generation and replacement via rendering/erasure decomposition, ORPE for layout fidelity, RAS for clean erasure, and the new TextWand-Bench dataset, claiming superior accuracy and quality over prior models.
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POCA: Pareto-Optimal Curriculum Alignment for Visual Text Generation
POCA combines Pareto optimization with curriculum alignment to improve multi-reward reinforcement learning for visual text generation without relying on weighted sums.