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Tuning-Free Noise Rectification for High Fidelity Image-to-Video Generation

Open clarencechen opened this issue 1 year ago • 6 comments

Model/Pipeline/Scheduler description

Applying pretrained Text-to-Video (T2V) Diffusion models to Image-to-video (I2V) generation tasks using SDEdit often results in low source image fidelity in open domains. This method achieves high source image fidelity in output videos through supplementing more precise source image information using noise interpolation during early denoising steps, resulting in a simple-to-implement, tuning-free, and plug-and-play implementation. The experimental results demonstrate the effectiveness in improving the source image fidelity of generated videos when applied to I2V generation using SDEdit with several different T2V models.

Open source status

  • [ ] The model implementation is available.
  • [ ] The model weights are available (Only relevant if addition is not a scheduler).

Provide useful links for the implementation

Website: https://noise-rectification.github.io/ Paper: https://arxiv.org/pdf/2403.02827.pdf

clarencechen avatar Mar 14 '24 23:03 clarencechen

@sayakpaul I'd take this on, if okay with you!

UmerHA avatar Mar 16 '24 10:03 UmerHA

Aure. Let's start with a community pipeline.

sayakpaul avatar Mar 17 '24 15:03 sayakpaul

Update: The model implementation is currently not openly available. I've asked the authors if they would consider open-sourcing the model.

UmerHA avatar Mar 19 '24 14:03 UmerHA

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the contributing guidelines are likely to be ignored.

github-actions[bot] avatar Apr 14 '24 15:04 github-actions[bot]

Update: Model implementation kindly been open sourced. ~~I plan to implement this soon.~~ Edit: I won't be able to do it, as another much more important (to me) project came up. Hopy another contributor takes a shot!

UmerHA avatar Apr 14 '24 15:04 UmerHA

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the contributing guidelines are likely to be ignored.

github-actions[bot] avatar May 12 '24 15:05 github-actions[bot]

@sayakpaul I'd like to take this up. if okay with you?

abhiramvad avatar Aug 07 '24 14:08 abhiramvad

@abhiramvad Thanks, feel free to take it up! You can add it to the community folder with your name & contribution to the community README.

a-r-r-o-w avatar Aug 30 '24 11:08 a-r-r-o-w

Thank you @a-r-r-o-w ! Taking this up.

abhiramvad avatar Aug 30 '24 14:08 abhiramvad

I have added changes to my fork, but I see a few GitHub workflows failing. May I know which ones are essential before I raise a PR?

abhiramvad avatar Sep 13 '24 02:09 abhiramvad

Form my experience: Some workflows fail because they require the use of HuggingFace resources, which external accounts don't have. If you open a PR, they'll likely work on the HF repo.

So as long as all tests pass & you've run linting, you should open a PR

UmerHA avatar Sep 13 '24 14:09 UmerHA

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the contributing guidelines are likely to be ignored.

github-actions[bot] avatar Oct 07 '24 15:10 github-actions[bot]