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Denoising

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하위 태스크: 6
평가표: 6
보존된 평가 기록: 15

Denoising is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of denoising is to recover the original image, which is considered to be noise-free, from a noisy observation.

<span style="color:grey; opacity: 0.6">( Image credit: Beyond a Gaussian Denoiser )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/awasthiabhijeet/Learning-From-Rules

공식 코드

Learning from Rules Generalizing Labeled Exemplars

https://github.com/aws/random-cut-forest-by-aws

공식 코드

Streaming Anomaly Detection

https://github.com/axeldavy/vnlnet

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Non-Local Video Denoising by CNN

https://github.com/axgoujon/convex_ridge_regularizers

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A Neural-Network-Based Convex Regularizer for Inverse Problems

https://github.com/b-remy/score-estimation-comparison

공식 코드

Denoising Score-Matching for Uncertainty Quantification in Inverse Problems

https://github.com/b010001y/prodiff

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ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation

https://github.com/bachzz/uw-diffphys

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Underwater Image Enhancement with Physical-based Denoising Diffusion Implicit Models

https://github.com/badr-moufad/dcps

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Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors

https://github.com/badr-moufad/mgdm

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A Mixture-Based Framework for Guiding Diffusion Models

https://github.com/bahjat-kawar/ddrm

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Denoising Diffusion Restoration Models

https://github.com/bahjat-kawar/ddrm-jpeg

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JPEG Artifact Correction using Denoising Diffusion Restoration Models

https://github.com/bahjat-kawar/enhancing-diffusion-robust

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Enhancing Diffusion-Based Image Synthesis with Robust Classifier Guidance

https://github.com/balbasty/nitorch

공식 코드

Model-based multi-parameter mapping

https://github.com/bald6354/tore_volumes

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Time-Ordered Recent Event (TORE) Volumes for Event Cameras

https://github.com/balintmate/neural-thermodynamic-integration

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Neural Thermodynamic Integration: Free Energies from Energy-based Diffusion Models

https://github.com/bansal-vansh/rectified-flow

공식 코드

On the Wasserstein Convergence and Straightness of Rectified Flow

https://github.com/bardiakh/syntheticallyenhanced

공식 코드

Synthetically Enhanced: Unveiling Synthetic Data's Potential in Medical Imaging Research

https://github.com/basiclab/unraveling-information-mix-ups

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A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding Optimization

https://github.com/batuceng/diffusion-layer-robustness-pc

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PCLD: Point Cloud Layerwise Diffusion for Adversarial Purification

https://github.com/bayesflow-org/consistency-model-posterior-estimation

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Consistency Models for Scalable and Fast Simulation-Based Inference

https://github.com/bbbbbbzhou/fedftn

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FedFTN: Personalized Federated Learning with Deep Feature Transformation Network for Multi-institutional Low-count PET Denoising

https://github.com/bcmi/DCI-VTON-Virtual-Try-On

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Taming the Power of Diffusion Models for High-Quality Virtual Try-On with Appearance Flow

https://github.com/bebebe666/optimalsteps

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Optimal Stepsize for Diffusion Sampling

https://github.com/bemc22/GeneralizedR2R

공식 코드

Generalized Recorrupted-to-Recorrupted: Self-Supervised Learning Beyond Gaussian Noise

https://github.com/benMen87/AppriximateConvolutionalSparseCoding

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Learned Convolutional Sparse Coding

https://github.com/benediktfesl/diffusion_mse

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On the Asymptotic Mean Square Error Optimality of Diffusion Models

https://github.com/benediktkol/recursive-noise-diffusion

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Multi-Class Segmentation from Aerial Views using Recursive Noise Diffusion

https://github.com/berkels/msiplib

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A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentation

https://github.com/berkiskender/RED-PSM

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RED-PSM: Regularization by Denoising of Factorized Low Rank Models for Dynamic Imaging

https://github.com/betterzhou/DECL

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Denoising-Aware Contrastive Learning for Noisy Time Series

https://github.com/bghojogh/Curvature-Anomaly-Detection

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Anomaly Detection and Prototype Selection Using Polyhedron Curvature

https://github.com/bguedj/cobra_denoising

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Non-linear aggregation of filters to improve image denoising

https://github.com/bhyang/diffusion-es

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Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction Following

https://github.com/bichunyang419/deedsr

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DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable Diffusion

https://github.com/bilocq/trust-the-critics-2

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A new method for determining Wasserstein 1 optimal transport maps from Kantorovich potentials, with deep learning applications

https://github.com/bilocq/wgan-gp-benchmark

공식 코드

A new method for determining Wasserstein 1 optimal transport maps from Kantorovich potentials, with deep learning applications

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