README.md

---
task_categories:
- video-text-to-text
language:
- en
license: cc-by-nc-4.0
tags:
- instructional-videos
- procedure-planning
- diffusion-models
---

# Masked Temporal Interpolation Diffusion (MTID) Dataset for Procedure Planning

This repository contains the datasets used in the paper [Masked Temporal Interpolation Diffusion for Procedure Planning in Instructional Videos](https://huggingface.co/papers/2507.03393).

The **MTID** (Masked Temporal Interpolation Diffusion) model addresses the challenge of procedure planning in instructional videos. It aims to generate coherent and task-aligned action sequences from start and end visual observations by leveraging a latent space temporal interpolation module to augment visual supervision with richer mid-state details. This dataset facilitates research and development in this area by providing necessary data for training and evaluating such models.

The code for the MTID model is available at: [https://github.com/WiserZhou/MTID](https://github.com/WiserZhou/MTID)

## Data Preparation

This dataset includes data for three widely used benchmark datasets: CrossTask, COIN, and NIV.

To download datasets and features, navigate to the respective dataset directory and run the download script as shown in the original repository:

```bash
cd ./dataset/{dataset_name}
bash download.sh
```

Replace `{dataset_name}` with `crosstask`, `coin`, or `NIV`.

Alternatively, you can find the datasets within this Hugging Face repository itself.

## Citation

If you find this dataset or the associated paper useful in your research, please cite:

```bibtex
@inproceedings{
  zhou2025masked,
  title={Masked Temporal Interpolation Diffusion for Procedure Planning in Instructional Videos},
  author={Yufan Zhou and Zhaobo Qi and Lingshuai Lin and Junqi Jing and Tingting Chai and Beichen Zhang and Shuhui Wang and Weigang Zhang},
  booktitle={ICLR},
  year={2025},
}
```