pavlo-melnyk/mlgp-embedme

The official implementation of the "Embed Me If You Can: A Geometric Perceptron" paper, Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 1276-1284.

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Emerging

This project provides an advanced method for classifying and understanding complex data patterns, specifically focusing on visual or geometrically structured information. It takes in structured datasets (like images or geometric shapes) and outputs classifications and visualizations of how the model interprets these patterns. Researchers in machine learning and computer vision would use this to explore novel ways of data representation and classification.

No commits in the last 6 months.

Use this if you are a researcher or academic exploring advanced geometric deep learning models for classification tasks and want to replicate or build upon the 'Embed Me If You Can: A Geometric Perceptron' paper.

Not ideal if you are looking for a plug-and-play solution for general image classification or a tool for non-research-oriented data analysis.

geometric deep learning computer vision research pattern recognition data embedding machine learning research
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 13 / 25

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Stars

9

Forks

2

Language

Jupyter Notebook

License

MIT

Last pushed

Jun 15, 2022

Commits (30d)

0

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