Devi Parikh
Description: Project webpage for fdd-video-edit
generative ai (303) diffusion models (35) video-to-video (3)
Paper arXiv Benchmark * Equal Contribution In an aquarium Sitting on a red bench Set it in winter wonderland Replace with a panda In Minecraft style Paint it pink and blue Abstract We introduce Emu Video Edit (EVE), a model that establishes a new state-of-the art in video editing without relying on any supervised video editing data. To develop EVE we separately train an image editing adapter and a video generation adapter, and attach both to the same text-to-image model. Then, to align the adapters towards
A comparison of our model with the previous state-of-the-art, InstructVid2Vid, on TGVE+
We extend our gratitude to the following people for their contributions (alphabetical order): Andrew Brown, Bichen Wu, Ishan Misra, Saketh Rambhatla, Xiaoliang Dai, Zijian He.
Devi Parikh