ParallelEdits: Efficient Multi-Aspect Text-Driven Image Editing with Attention Grouping

Neural Information Processing Systems 

Text-driven image synthesis has made significant advancements with the development of diffusion models, transforming how visual content is generated from text prompts. Despite these advances, text-driven image editing, a key area in computer graphics, faces unique challenges. A major challenge is making simultaneous edits across multiple objects or attributes.

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