IVUlab/RSMMVP

Remote Sensing MMVP

This dataset follows a similar procedure to the original MMVP benchmark on natural images but directed towards the remote sensing domain. Challenging visual patterns are identified based on CLIP blind pairs, accompanied with the correpsonding questions, options and ground-truth answer.

Authors:

Abduljaleel Adejumo*, Faegheh Yeganli*, Clifford Broni-Bediako, Aoran Xiao, Naoto Yokoya**, Mennatullah Siam**

• Symbol:* denotes equal contribution
• Symbol:** denotes equally advising

Acknowledgements:

We acknowledge that images within this dataset are used from the publicly available Geochat dataset: https://huggingface.co/datasets/MBZUAI/GeoChat_Instruct

References

@article{adejumo2025vision,
  title={A Vision Centric Remote Sensing Benchmark},
  author={Adejumo, Abduljaleel and Yeganli, Faegheh and Broni-bediako, Clifford and Xiao, Aoran and Yokoya, Naoto and Siam, Mennatullah},
  journal={arXiv preprint arXiv:2503.15816},
  year={2025}
}