joaodaniel/rs-clip-cap4

CLIP ViT-Large finetuned with Remote Sensing data

This is a CLIP model of size Large that finetuned with Remote Sensing data, namely using image captioning datasets.

The original weights are from openai/clip-vit-large-patch14.

Model Details

Model Description

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This model was finetuned with the typical contrastive learning objective to train CLIP models.

Training Data:

Bias, Risks, and Limitations

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The model may inherit the biases and limitations from the original CLIP weights.

While being trained with Remote Sensing data, it can still be limited to downstream applications of this domain, due to the nature of the training data (images of low resolution, descriptions that are too short, can contain mistakes, or are overly generic.)

How to Get Started with the Model

Your typical huggingface interface for CLIP Models: https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPModel

Citation

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> This model was developed with regards to the following work. If useful, please cite us at:

@article{silva2024large,
  title={Large language models for captioning and retrieving remote sensing images},
  author={Silva, Jo{\~a}o Daniel and Magalh{\~a}es, Jo{\~a}o and Tuia, Devis and Martins, Bruno},
  journal={arXiv preprint arXiv:2402.06475},
  year={2024}
}

Model Card Authors

João Daniel Silva - https://github.com/DannielSilva