Verify evals on Papers with Code
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- Dominant language
- Python
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Description
Hi,
Niels here from the open-source team at Hugging Face. Congratulations on your work!
I've made the paper and 3 paper-native evaluations available on Papers with Code.
The paper has results on Depth estimation, Image Matting, and Surface Normal Estimation task pages.
The DAViD Large results currently rank second on Goliath (Relative Depth) and PhotoMatte85.
The DAViD Large result currently ranks third on Hi4D.
Would it be possible to verify these results and let me know if any score, model name, benchmark protocol, or openness metadata should be corrected?
You can also edit the task, methods, project page, and GitHub URL directly from the paper page using your Hugging Face account.
If you'd like to showcase the results in your repository README, you can copy these live leaderboard badges (or use the “Copy PwC badge” button in the Results section):
Kind regards,
Niels
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 with the linked paper and its three Papers with Code task and benchmark pages: Goliath, PhotoMatte85, and Hi4D. Compare the DAViD Large entries with the paper and repository information, checking each score, model name, benchmark protocol, and openness metadata. Done means reporting any corrections needed, with optional README badges based on the verified results.
Written by the indexing model from the issue text.
Assessment
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Active
- Clarity
- Mostly clear
- Newbie friendliness
- 50/100