12 papers with code • 0 benchmarks • 0 datasets
This work presents Kornia -- an open source computer vision library which consists of a set of differentiable routines and modules to solve generic computer vision problems.
This paper proposes a deep neural network structure that exploits edge information in addressing representative low-level vision tasks such as layer separation and image filtering.
The effectiveness and superior performance of our approach are validated through comprehensive experiments in a range of applications.
In this paper, a non-convex non-smooth optimization framework is proposed to achieve diverse smoothing natures where even contradictive smoothing behaviors can be achieved.
We introduce a bottom-up model for simultaneously finding many boundary elements in an image, including contours, corners and junctions.