aigc-apps / aigc-apps/VideoX-Fun
CogVideoX 1.1 may have improved motion, but quality is behind I2v/Interpolation
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- Dominant language
- Python
- Stars
- 2.3k
- Forks
- 188
- Avg merge
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- Merged PRs (30d)
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Description
I2V and the latest https://github.com/feizc/CogvideX-Interpolation models which is a fine-tune of the official I2V are just better at coherent motion provided a frame. However, these models have significant limitations with resolution and frame length... things CogVideoX-Fun solves.
What is the process of creating a "fun" version of a CogVideoX model like Interpolation? May you guys please consider doing a "Fun" version of the https://github.com/feizc/CogvideX-Interpolation finetune please?
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No project files, tests, or training entry points are identified in the issue. Start by reviewing VideoX-Fun's documented model-training process and compare it with the CogVideoX-Interpolation models; done would mean establishing a feasible process or delivering a compatible Fun fine-tune with its limitations documented.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100