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Emu Video: Factorizing Text-to-Video Generation by Explicit Image Conditioning
We present Emu Video, a text-to-video generation model that factorizes the generation into two steps: first generating an image conditioned on the text, and then generating a video conditioned on the text and the generated image.
Make-An-Animation: Large-Scale Text-conditional 3D Human Motion Generation
However, existing approaches are limited by their reliance on relatively small-scale motion capture data, leading to poor performance on more diverse, in-the-wild prompts.
Ranked #20 on
Motion Synthesis
on HumanML3D
Text-Conditional Contextualized Avatars For Zero-Shot Personalization
Recent large-scale text-to-image generation models have made significant improvements in the quality, realism, and diversity of the synthesized images and enable users to control the created content through language.
