Improve model card: Add pipeline tag, library_name, paper, and project page links

README.md

@@ -1,7 +1,7 @@
 ---
-license: mit
 language:
 - en
+license: mit
 metrics:
 - mean_iou
 - AbsRel
@@ -9,23 +9,47 @@ metrics:
 tags:
 - Semantic_Future_Prediction
 - World Models
+pipeline_tag: image-feature-extraction
+library_name: pytorch
 ---
 
 # DINO-Foresight: Looking into the Future with DINO (NeurIPS 2025)
 
 ![image](https://cdn-uploads.huggingface.co/production/uploads/677272184d148b904333e874/btsV1EHK4yYiyboMjG7oj.png)
 
+DINO-Foresight is a novel framework that operates in the semantic feature space of pretrained Vision Foundation Models (VFMs) to predict future dynamics. It trains a masked feature transformer in a self-supervised manner to forecast the evolution of VFM features over time, enabling various scene understanding tasks through off-the-shelf, task-specific heads.
+
+## Paper
+[DINO-Foresight: Looking into the Future with DINO](https://huggingface.co/papers/2412.11673)
+
+## Project Page
+[https://dino-foresight.github.io](https://dino-foresight.github.io)
+
+## Code
+The official implementation can be found on GitHub: [https://github.com/Sta8is/DINO-Foresight](https://github.com/Sta8is/DINO-Foresight)
+
+## Sample Usage
+
+The model is built with PyTorch. You can set up the environment and install dependencies as follows:
+
+```bash
+conda create -n dinof python=3.11
+conda activate dinof
+pip install torch==2.2.0 torchvision==0.17.0 torchaudio==2.2.0 --index-url https://download.pytorch.org/whl/cu121   
+git clone https://github.com/Sta8is/DINO-Foresight
+cd DINO-Foresight
+pip install -r requirements.txt
+```
 
-# Code
-https://github.com/Sta8is/DINO-Foresight
+For detailed usage examples and model training, refer to the provided demos and the GitHub repository.
 
-# Demo:
+## Demo
 We provide 2 quick demos.
 
 - [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1K8o3-zkR5lCdAv7Qjz7rhWP8n2VrFOdz?usp=sharing)
 - [Demo](https://github.com/Sta8is/DINO-Foresight/blob/main/demo.ipynb).
 
-# Citation
+## Citation
 If you found DINO-Foresight useful in your research, please consider starring ⭐ us on GitHub and citing 📚 us in your research!
 ```bibtex
 @inproceedings{karypidis2025dinoforesight,
@@ -37,5 +61,5 @@ url={https://arxiv.org/abs/2412.11673}
 }
 ```
 
-# Acknowledgements
-Our code is partially based on [Maskgit-pytorch](https://github.com/valeoai/Maskgit-pytorch), a pytorch implementation of MaskedGit by ValeoAI. We also thank authors of [DINOv2](https://github.com/facebookresearch/dinov2), [DPT](https://github.com/isl-org/DPT), [DepthAnythingV2](https://github.com/DepthAnything/Depth-Anything-V2), [LOTUS](https://github.com/EnVision-Research/Lotus) for their work and open-source code.
+## Acknowledgements
+Our code is partially based on [Maskgit-pytorch](https://github.com/valeoai/Maskgit-pytorch), a pytorch implementation of MaskedGit by ValeoAI. We also thank authors of [DINOv2](https://github.com/facebookresearch/dinov2), [DPT](https://github.com/isl-org/DPT), [DepthAnythingV2](https://github.com/DepthAnything/Depth-Anything-V2), [LOTUS](https://github.com/EnVision-Research/Lotus) for their work and open-source code.