Emu Video and Emu Edit
Meta releases Emu Video and Emu Edit, a pair of diffusion models targeting controlled text-to-video generation and instruction-based image editing.
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Emu Video: Generates high-quality video from text-only, image-only, or combined text + image inputs using a factorized diffusion approach - text-to-image followed by image-conditioned video.
Emu Edit: Enables free-form image editing through text instructions, handling region, local, and global edits within one model.
Factorized video: The text-to-image then image-to-video split dramatically cuts training cost and improves controllability compared to end-to-end T2V models.
Unified research line: Both models extend Meta's Emu foundation family, pointing toward a unified multimodal generative stack shared across image, video, and edit tasks.