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jerpelhan

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GECO2-demo

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Running on Zero

I am writing to apply for a GPU grant in support of GeCo2, an advanced exemplar-based object detection and counting system which was recently accepted to AAAI26 (link).

GeCo2, currently under review, introduces a multiscale reformulation that makes the model much faster, more memory-efficient, and more accurate than the original version. It has been trained on numerous public detection datasets, providing strong generalization across a wide range of visual scenarios.

A user can, in an interactive demo, delineate an exemplar object in one image, and the model will automatically detect all occurrences of that object category. This enables powerful exemplar-based detection and counting in dense or few-shot settings. I plan to make this functionality easily accessible through a Gradio Space, allowing the community to explore and use the model with no technical barriers.

GPU support is essential for GeCo2 to work. We have already tested the system on a T4 and confirmed it runs efficiently. The space is currently set to free CPU, but it does not work due to a lack of GPU credits.

Your support through a Hugging Face Spaces GPU grant would enable us to deploy GeCo2 openly for the research and developer community, advancing the state of exemplar-based detection and making this next-generation model widely accessible.

Thank you for your time and consideration!

Some examples on novel categories