grigorisg9gr/polynomial_nets
Official Implementation of the CVPR'20 paper 'Π-nets: Deep Polynomial Neural Networks' and its T-PAMI-21 extension.
This project offers an alternative way to build and train deep neural networks, providing a foundation for creating more efficient and effective AI models. It takes various data inputs, like images or 3D mesh data, and processes them to produce improved results in tasks such as face recognition, image generation, and 3D shape analysis. Researchers and advanced practitioners in computer vision and machine learning would use this to explore novel neural network architectures.
176 stars. No commits in the last 6 months.
Use this if you are a researcher or advanced practitioner experimenting with new neural network architectures for computer vision tasks and want to explore polynomial-based deep learning models.
Not ideal if you are looking for a plug-and-play solution for common machine learning problems without delving into core model architecture research.
Stars
176
Forks
27
Language
Python
License
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Category
Last pushed
Jan 06, 2023
Commits (30d)
0
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