Add comprehensive dataset card for MTID dataset (#1)

- Add comprehensive dataset card for MTID dataset (d28eafb1ca3c9649d50ab45194802d38408381a3)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -0,0 +1,48 @@
+---
+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},
+}
+```