image smoothing
19 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in image smoothing
Most implemented papers
Differentiable Data Augmentation with Kornia
In this paper we present a review of the Kornia differentiable data augmentation (DDA) module for both for spatial (2D) and volumetric (3D) tensors.
Field of Junctions: Extracting Boundary Structure at Low SNR
We introduce a bottom-up model for simultaneously finding many boundary elements in an image, including contours, corners and junctions.
A Generalized Framework for Edge-preserving and Structure-preserving Image Smoothing
The effectiveness and superior performance of our approach are validated through comprehensive experiments in a range of applications.
AugStatic - A Light-Weight Image Augmentation Library
AugStatic is a custom-built image augmentation library with lower computation costs and more extraordinary salient features compared to other image augmentation libraries.
Augmented Balanced Image Dataset Generator Using AugStatic Library
This paper focuses on the image dataset generator that balances an imbalanced dataset using the AugStatic augmentation library.
Contrastive Semantic-Guided Image Smoothing Network
Image smoothing is a fundamental low-level vision task that aims to preserve salient structures of an image while removing insignificant details.
Difference of Anisotropic and Isotropic TV for Segmentation under Blur and Poisson Noise
In this paper, we aim to segment an image degraded by blur and Poisson noise.
OSRE: Object-to-Spot Rotation Estimation for Bike Parking Assessment
However, estimating object rotation with respect to other visual objects in the visual context of an input image still lacks deep studies due to the unavailability of object datasets with rotation annotations.
A Complementary Global and Local Knowledge Network for Ultrasound denoising with Fine-grained Refinement
However, the presence of speckle noise in ultrasound images invariably degrades image quality, impeding the performance of subsequent tasks, such as segmentation and classification.