image smoothing
19 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in image smoothing
Most implemented papers
Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
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.
Deep PCB To COCO Convertor
It has 1500 image pairs.
A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing
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.
Decouple Learning for Parameterized Image Operators
Many different deep networks have been used to approximate, accelerate or improve traditional image operators, such as image smoothing, super-resolution and denoising.
Image Smoothing via Unsupervised Learning
Image smoothing represents a fundamental component of many disparate computer vision and graphics applications.
A Benchmark for Edge-Preserving Image Smoothing
This benchmark includes an image dataset with groundtruth image smoothing results as well as baseline algorithms that can generate competitive edge-preserving smoothing results for a wide range of image contents.
Side Window Filtering
In addition to image filtering, we further show that the SWF principle can be extended to other applications involving the use of a local window.
A Generalized Framework for Edge-preserving and Structure-preserving Image Smoothing
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.
Concurrently Extrapolating and Interpolating Networks for Continuous Model Generation
Most deep image smoothing operators are always trained repetitively when different explicit structure-texture pairs are employed as label images for each algorithm configured with different parameters.
Image Smoothing Algorithm Based on Gradient Analysis
As additional measure that helps to discriminate the types of boundaries inverted gradient values were used.