patrikhuber/superviseddescent
A C++11 library implementing supervised descent optimization with a focus on facial landmark detection.
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This library provides a generic implementation of the supervised descent method, a machine learning optimization technique that can work with non-differentiable functions. It features a pre-trained facial landmark detection model based on Robust Cascaded Regression. The implementation uses Eigen for efficient matrix operations and is delivered as a header-only library for easy integration.
Frequently asked
- What is patrikhuber/superviseddescent?
- A C++11 library implementing supervised descent optimization with a focus on facial landmark detection.
- Is superviseddescent open source?
- Yes — patrikhuber/superviseddescent is open source, released under the Apache-2.0 license.
- What language is superviseddescent written in?
- patrikhuber/superviseddescent is primarily written in C++.
- How popular is superviseddescent?
- patrikhuber/superviseddescent has 406 stars on GitHub.
- Where can I find superviseddescent?
- patrikhuber/superviseddescent is on GitHub at https://github.com/patrikhuber/superviseddescent.