Add Support for I3D and C3D Features and Clarify Validation Splits for ActivityNet Dataset
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- Dominant language
- Python
- Stars
- 269
- Forks
- 20
- Avg merge
- 7h 3m
- Merged PRs (30d)
- 2
Description
Currently, the library only supports `Resnet_Glove`, `CLIP`, and `CLIP_Slowfast` features for the ActivityNet and Charades datasets. However, several papers use other feature types, such as `I3D` (for Charades-STA) and `C3D` (for ActivityNet), as noted in Table 2 of the EaTR paper ([link to paper](https://openreview.net/pdf?id=ZpfIFuOPDy)). Expanding support to include these features would align with a broader range of existing research.
Additionally, I noticed that for ActivityNet, many works report results on the `val_2` split, while here only the `val` split is provided, which I believe corresponds to `val_1`. Could you clarify this aspect? How can I access to `val_2` split?
Thank you for your efforts in creating this unified framework—it’s much appreciated!
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
Start by tracing how existing ActivityNet and Charades feature types and validation splits are configured. Compare the current behavior with the I3D, C3D, and val_2 requirements described in the issue; done means the requested feature types are supported and the val_2 access or limitation is clearly resolved.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100