Implementation of Phenaki Video, which uses Mask GIT to produce text-guided videos of up to 2 minutes in length, in Pytorch. It will also combine another technique involving a token critic for potentially even better generations. A new paper suggests that instead of relying on the predicted probabilities of each token as a measure of confidence, one can train an extra critic to decide what to iteratively mask during sampling. This repository will also endeavor to allow the researcher to train on text-to-image and then text-to-video. Similarly, for unconditional training, the researcher should be able to first train on images and then fine tune on video.
Features
- Implementation of Phenaki Video
- Uses Mask GIT to produce text guided videos
- Videos of up to 2 minutes in length
- Combines techniques involving a token critic for potentially even better generations
- You can optionally train this critic for potentially better generations
- This repository will also endeavor to allow the researcher to train on text-to-image and then text-to-video
License
MIT LicenseFollow Phenaki - Pytorch
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