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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/anytop2025/anytop

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AnyTop: Character Animation Diffusion with Any Topology

https://github.com/apple/ml-destseg

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DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly Detection

https://github.com/apple/ml-diffucoder

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DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation

https://github.com/apple/ml-planner

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PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model

https://github.com/apple1986/morsecodeimageclassify

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Noise Adaption Network for Morse Code Image Classification

https://github.com/aqlaboratory/genie

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Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Clouds

https://github.com/archerfmy/sd-t2i-360panoimage

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Diffusion360: Seamless 360 Degree Panoramic Image Generation based on Diffusion Models

https://github.com/ari-dasci/autoencoder-case-studies

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An analysis on the use of autoencoders for representation learning: fundamentals, learning task case studies, explainability and challenges

https://github.com/ari-dasci/autoencoder-showcase

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A Showcase of the Use of Autoencoders in Feature Learning Applications

https://github.com/ariG23498/G-SimCLR

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G-SimCLR: Self-Supervised Contrastive Learning with Guided Projection via Pseudo Labelling

https://github.com/arimousa/DDAD

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Anomaly Detection with Conditioned Denoising Diffusion Models

https://github.com/arnisha-k/instance-specific-param

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Learning Instance-Specific Parameters of Black-Box Models Using Differentiable Surrogates

https://github.com/arnupretorius/lindaedynamics_icml2018

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Learning Dynamics of Linear Denoising Autoencoders

https://github.com/arsedler9/lfads-torch

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lfads-torch: A modular and extensible implementation of latent factor analysis via dynamical systems

https://github.com/articulatory/articulatory

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Deep Speech Synthesis from MRI-Based Articulatory Representations

https://github.com/ary4n99/llm-robustness

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Enhancing LLM Robustness to Perturbed Instructions: An Empirical Study

https://github.com/asdvfghg/classbd

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Classifier-guided neural blind deconvolution: a physics-informed denoising module for bearing fault diagnosis under heavy noise

https://github.com/aselsan-research-imaging-team/flight-net

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FLIGHT Mode On: A Feather-Light Network for Low-Light Image Enhancement

https://github.com/ask-berkeley/om-tps

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Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional

https://github.com/asleepytree/eb-cache

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Exposure Bias Reduction for Enhancing Diffusion Transformer Feature Caching

https://github.com/asperti/Embedding-in-Diffusion-Models

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Image Embedding for Denoising Generative Models

https://github.com/astaka-pe/DeepMeshPrior

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Deep Mesh Prior: Unsupervised Mesh Restoration using Graph Convolutional Networks

https://github.com/astra-vision/stablemtl

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StableMTL: Repurposing Latent Diffusion Models for Multi-Task Learning from Partially Annotated Synthetic Datasets

https://github.com/astrodatalab/li2024_public

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Using Galaxy Evolution as Source of Physics-Based Ground Truth for Generative Models

https://github.com/astrodatalab/lizarraga_2024

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Understanding Galaxy Morphology Evolution Through Cosmic Time via Redshift Conditioned Diffusion Models

https://github.com/atenrev/diffusion_continual_learning

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Continual Learning of Diffusion Models with Generative Distillation

https://github.com/atenrev/difussion_continual_learning

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Continual Learning of Diffusion Models with Generative Distillation

https://github.com/atik666/NMformer

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NMformer: A Transformer for Noisy Modulation Classification in Wireless Communication

https://github.com/atik666/denomae

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DenoMAE: A Multimodal Autoencoder for Denoising Modulation Signals

https://github.com/atomicarchitects/dens

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Generalizing Denoising to Non-Equilibrium Structures Improves Equivariant Force Fields

https://github.com/aupendu/SelfEnNet

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Self-supervision via Controlled Transformation and Unpaired Self-conditioning for Low-light Image Enhancement

https://github.com/aurangau/ICIP2024

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A Dictionary Based Approach for Removing Out-of-Focus Blur

https://github.com/auto-dog/moac_deep

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Misaligned Over-The-Air Computation of Multi-Sensor Data with Wiener-Denoiser Network

https://github.com/avinashpaliwal/MaskDnGAN

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Multi-Stage Raw Video Denoising with Adversarial Loss and Gradient Mask

https://github.com/avisekiit/TCSVT-LightWeight-CNNs

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Lightweight Modules for Efficient Deep Learning based Image Restoration

https://github.com/awaisrauf/xray-denoising

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Leveraging Deep Stein's Unbiased Risk Estimator for Unsupervised X-ray Denoising

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