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Apply for community grant: Academic project (gpu)
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 (NVIDIA T4 Small) 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
