GranD

GranD - Grounding Anything Dataset

GLaMM: Pixel Grounding Large Multimodal Model (CVPR 2024)

GranD-f Dataset
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Citation

@article{hanoona2023GLaMM,
title={GLaMM: Pixel Grounding Large Multimodal Model},
author={Rasheed, Hanoona and Maaz, Muhammad and Shaji, Sahal and Shaker, Abdelrahman and Khan, Salman and Cholakkal, Hisham and Anwer, Rao M. and Xing, Eric and Yang, Ming-Hsuan and Khan, Fahad S.},
journal={The IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year={2024}
}

Contribute to the GranD Dataset

The GranD dataset offers densely annotated data, acquired through an automated annotation pipeline that leverages state-of-the-art (SOTA) vision and V-L models. We extend our thanks to the authors of these models for open-sourcing their work, making it accessible to the research community. Despite the efficiency of our pipeline, we acknowledge its imperfections. We invite researchers and developers to contribute models or methods that may enhance the dataset's accuracy and overall quality. If you have newer, more advanced models, or if you wish to contribute in any way, kindly submit a pull request on our GitHub page or contact us directly at hanoona.bangalath@mbzuai.ac.ae or muhammad.maaz@mbzuai.ac.ae. Thank you.