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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/scottdyt/sgdl

공식 코드

Self-Guided Learning to Denoise for Robust Recommendation

https://github.com/scraed/CharacteristicGuidanceWebUI

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Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance Scale

https://github.com/scuwyh2000/diff-ii

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Inversion Circle Interpolation: Diffusion-based Image Augmentation for Data-scarce Classification

https://github.com/sdittmer/gtfd

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Ground Truth Free Denoising by Optimal Transport

https://github.com/sdittmer/von_Neumann_Projection_Architecture

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A Projectional Ansatz to Reconstruction

https://github.com/sdl-asu/acla

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Adaptive Cross-Layer Attention for Image Restoration

https://github.com/sebulo/PuTT

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Coarse-To-Fine Tensor Trains for Compact Visual Representations

https://github.com/securefederatedai/openfl

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Federated Discrete Denoising Diffusion Model for Molecular Generation with OpenFL

https://github.com/seeker98/crwkv

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Multi-View Learning with Context-Guided Receptance for Image Denoising

https://github.com/senmaoy/Score-Mismatching

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Score Mismatching for Generative Modeling

https://github.com/sensorsini/dnd_hls

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Within-Camera Multilayer Perceptron DVS Denoising

https://github.com/sentient-codebot/EnergyDiff-pub

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EnergyDiff: Universal Time-Series Energy Data Generation using Diffusion Models

https://github.com/seokhyeonhong/salad

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SALAD: Skeleton-aware Latent Diffusion for Text-driven Motion Generation and Editing

https://github.com/sepkfr/fine-grained-gaussian-process-forcating

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Fine-grained Forecasting Models Via Gaussian Process Blurring Effect

https://github.com/sergulaydore/Feature-Grouping-Regularizer

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Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data

https://github.com/sethnabarro/gbp_learning

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Learning in Deep Factor Graphs with Gaussian Belief Propagation

https://github.com/seu-proactivesecurity-group/malpurifier

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MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion Attacks

https://github.com/sfm-sr-denoising/sfm

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Stochastic Frequency Masking to Improve Super-Resolution and Denoising Networks

https://github.com/shadyabh/udpm

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UDPM: Upsampling Diffusion Probabilistic Models

https://github.com/shaharlutatipersonal/ocd

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OCD: Learning to Overfit with Conditional Diffusion Models

https://github.com/shakeebmurtaza/tedloc

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TeD-Loc: Text Distillation for Weakly Supervised Object Localization

https://github.com/shams-mehdi/aib9_openmm

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A survey of probabilistic generative frameworks for molecular simulations

https://github.com/shaoyanpan/Full-dose-Whole-body-PET-Synthesis-from-Low-dose-PET-Using-Consistency-Model

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Full-dose Whole-body PET Synthesis from Low-dose PET Using High-efficiency Denoising Diffusion Probabilistic Model: PET Consistency Model

https://github.com/shaoyanpan/Synthetic-CT-generation-from-MRI-using-3D-transformer-based-denoising-diffusion-model

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Synthetic CT Generation from MRI using 3D Transformer-based Denoising Diffusion Model

https://github.com/sharan21/epaae

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Towards Robust and Semantically Organised Latent Representations for Unsupervised Text Style Transfer

https://github.com/sharif-apu/BJDD_CVPR21

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Beyond Joint Demosaicking and Denoising: An Image Processing Pipeline for a Pixel-bin Image Sensor

https://github.com/sharif-apu/DPE_JBHI

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Deep Perceptual Enhancement for Medical Image Analysis

https://github.com/sharif-apu/lsd-tfformer

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Illuminating Darkness: Enhancing Real-world Low-light Scenes with Smartphone Images

https://github.com/sharif-apu/twostageHDR_NTIRE21

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A Two-stage Deep Network for High Dynamic Range Image Reconstruction

https://github.com/shehzaidi/pre-training-via-denoising

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Pre-training via Denoising for Molecular Property Prediction

https://github.com/shen-lab/ebd

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Equivariant Blurring Diffusion for Hierarchical Molecular Conformer Generation

https://github.com/shenduke/saffn

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Structure Modeling Activation Free Fourier Network for Spacecraft Image Denoising

https://github.com/shentianxiao/text-autoencoders

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Educating Text Autoencoders: Latent Representation Guidance via Denoising

https://github.com/sherbret/DCT2net

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DCT2net: an interpretable shallow CNN for image denoising

https://github.com/sherbret/lichi

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Linear Combinations of Patches are Unreasonably Effective for Single-Image Denoising

https://github.com/sherbret/nl-ridge

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Towards a unified view of unsupervised non-local methods for image denoising: the NL-Ridge approach

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.