Include implementation of MViTV2-B and MViTV2-L models
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
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- Forks
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- Avg merge
- 1d 15h
- Merged PRs (30d)
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Description
🚀 The feature, motivation and pitch
Currently Pytorch includes an implementation of MViTV2-S, showing that the model is useful. MViTV2-B and MViTV2-L are even more powerful. Weights are publicly available at https://github.com/facebookresearch/SlowFast/blob/main/projects/mvitv2/README.md.
Alternatives
The SlowFast library has an implementation but it's hard to use outside of the slowfast library. Would be much much easier to have something built in to pytorch.
Additional context
No response
Contributor guide
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
Start by reading the existing MViTV2-S implementation in PyTorch and compare it with the MViTV2-B and MViTV2-L implementation and publicly available weights in the linked SlowFast README. Confirm the model scope and integration expectations before proceeding; done means both requested models are implemented in PyTorch with the referenced weights supported.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100