Elastica Model

Elastica models, which incorporate curvature-based regularization, offer advantages over traditional methods in various image processing tasks, such as inpainting and color regularization. Current research focuses on developing efficient algorithms, like hybrid alternating minimization, to overcome the computational challenges posed by the nonlinearity of these models, and on adapting them to different architectures, including transformers and convolutional neural networks. These improvements enhance the accuracy and speed of image processing, leading to applications in areas like audio classification and efficient deployment of vision transformers on mobile devices.