image smoothing

13 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

Kornia: an Open Source Differentiable Computer Vision Library for PyTorch

kornia/kornia 5 Oct 2019

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.

A Generic Deep Architecture for Single Image Reflection Removal and Image Smoothing

fqnchina/CEILNet ICCV 2017

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

fqnchina/DecoupleLearning ECCV 2018

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

fqnchina/ImageSmoothing 7 Nov 2018

Image smoothing represents a fundamental component of many disparate computer vision and graphics applications.

A Benchmark for Edge-Preserving Image Smoothing

zhufeida/Benchmark_EPS 2 Apr 2019

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

wang-kangkang/SideWindowFilter-pytorch CVPR 2019

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

wliusjtu/Generalized-Smoothing-Framework 23 Jul 2019

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

mdcnn/ 12 Jan 2020

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

Oxid15/Image-Smoothing-Algorithm-Based-on-Gradient-Analysis 16 Jun 2020

As additional measure that helps to discriminate the types of boundaries inverted gradient values were used.

Differentiable Data Augmentation with Kornia

arraiyopensource/kornia 19 Nov 2020

In this paper we present a review of the Kornia differentiable data augmentation (DDA) module for both for spatial (2D) and volumetric (3D) tensors.