yeungchenwa/Recommendations-Diffusion-Text-Image
A paper collection of recent diffusion models for text-image generation tasks, e,g., visual text generation, font generation, text removal, text image super resolution, text editing, handwritten generation, scene text recognition and scene text detection.
This is a curated collection of academic papers focused on advanced text and image generation techniques. It helps researchers and practitioners explore various methods for tasks like creating unique fonts, generating realistic text within images, restoring damaged documents, or editing existing text in visuals. The target audience includes AI/ML researchers, graphic designers interested in generative tools, and anyone involved in digital content creation or document preservation.
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Use this if you are a researcher or advanced practitioner seeking to understand the latest developments and papers in text-image diffusion models for tasks like font creation, visual text generation, or image restoration.
Not ideal if you are looking for ready-to-use software, code implementations, or a simple drag-and-drop tool to perform these tasks without diving into the underlying research.
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Dec 19, 2024
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