OpenImagingLab / OpenImagingLab/FlashVSR

Release VSR-120K on Hugging Face

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Python
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Description

Hi @JunhaoZhuang 🤗

I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2510.12747.
The paper page lets people discuss about your paper and lets them find artifacts about it (your dataset for instance),
you can also claim the paper as yours which will show up on your public profile at HF, add Github and project page URLs.

It's great to see that the FlashVSR model is already available on the Hugging Face Hub! I also noticed you've created a repository for the VSR-120K dataset on Hugging Face (https://huggingface.co/datasets/JunhaoZhuang/VSR-120K), but it's currently marked as "Coming Soon" / "Pending release".

Would you like to host the full VSR-120K dataset on https://huggingface.co/datasets?
Hosting on Hugging Face will give you more visibility/enable better discoverability, and will also allow people to do:

from datasets import load_dataset

dataset = load_dataset("JunhaoZhuang/VSR-120K")

If you're interested, leaving a guide here: https://huggingface.co/docs/datasets/loading.
We also support Webdataset, useful for image/video datasets: https://huggingface.co/docs/datasets/en/loading#webdataset.

Besides that, there's the dataset viewer which allows people to quickly explore the first few rows of the data in the browser.

After uploaded, we can also link the dataset to the paper page (read here) so people can discover your work.

Let me know if you're interested/need any guidance.

Kind regards,

Niels

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the VSR-120K dataset repository on Hugging Face and the linked datasets loading and WebDataset guides. Determine whether the full dataset is ready for hosting; done means it is released on the Hugging Face Hub and linked to the paper page.

Written by the indexing model from the issue text.

Assessment

Tech stack
huggingface, python
Domain
data, machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

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