Shift, Latently. The Newest approach for Text-to-Video Tactics
Latent-Shift is a cool new method for text-to-video AI generation. It uses a simpler approach than traditional tactics. Bottom line: Latent-Shift can turn casual photos or videos from your phone into lifelike, moving scenes.
I demonstrated some of these techniques last week here.
Taking a note from Andy Warhol, everyone will have their 15-mins of award-winning text-to-video generated movie moment. Right?
Diagram:
Here's a simple explanation of the framework:
An autoencoder is first trained on images to learn a hidden code or representation.
This autoencoder is then adjusted to work with video frames instead of just images.
During training, a special kind of U-Net learns to clean up the hidden video code at different points in time. When it's time to make a video, the U-Net cleans up the code step by step, starting with random noise and ending with a clear image.
The U-Net has two main parts: one with 2D layers (in violet) and another with attention layers (in gray). A red module helps shift information in time, which is added to the violet part. The text that we want to convert into a video is connected to the gray part.
In the end, the picture and video details are simplified for clarity.