PS
pschaldenbrand/Text2Video
A fast approach for translating a series of text prompts into a video. The 2022 NeurIPS Workshop on Machine Learning for Creativity and Design
Towards Real-Time Text2Video via CLIP-Guided, Pixel-Level Optimization
Peter Schaldenbrand, Zhixuan Liu, and Jean Oh. The Robotics Institute, Carnegie Mellon University
An approach to generating videos based on a series of given language descriptions of the video. We currently only have a Colab implementation which is linked above.
Please message Peter at pschalde at andrew dot cmu dot edu with any questions or make a GitHub issue. Thanks!