Emu Edit
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About
Emu Edit is a state-of-the-art multi-task image editing model developed by Meta, designed for instruction-based image editing. It adapts its architecture for various image editing tasks, including region-based, free-form editing, and computer vision tasks like detection and segmentation, all formulated as generative tasks. The model utilizes learned task embeddings to effectively steer the generation process towards the specific task. Emu Edit can swiftly adapt to new tasks, making it advantageous for scenarios with limited data. It also includes a publicly available benchmark featuring seven image editing tasks for rigorous evaluation of models like Emu Edit.
Platform
Task
Features
• new benchmark for image editing tasks
• learned task embeddings for steering generation
• few-shot learning with task inversion
• generative task formulation
• region-based and free-form editing
• multi-task image editing
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