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Found 5 papers, 1 papers with code
Dense Semantic Correspondence where Every Pixel is a Classifier
Determining dense semantic correspondences across objects and scenes is a difficult problem that underpins many higher-level computer vision algorithms.
Regression-Based Image Alignment for General Object Categories
Gradient-descent methods have exhibited fast and reliable performance for image alignment in the facial domain, but have largely been ignored by the broader vision community.
Why do linear SVMs trained on HOG features perform so well?
Linear Support Vector Machines trained on HOG features are now a de facto standard across many visual perception tasks.
Optimization Methods for Convolutional Sparse Coding
We discuss a range of optimization methods for solving the convolutional sparse coding objective, and the properties that make each method suitable for different applications.
Fast Convolutional Sparse Coding
Sparse coding has become an increasingly popular method in learning and vision for a variety of classification, reconstruction and coding tasks.
