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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/deepmind/deepmind-research

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Large-scale graph representation learning with very deep GNNs and self-supervision

https://github.com/deepmind/deepmind-research/tree/master/gated_linear_networks

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Gaussian Gated Linear Networks

https://github.com/deepsoftwareanalytics/kadel

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KADEL: Knowledge-Aware Denoising Learning for Commit Message Generation

https://github.com/deepxuan/dn-dp

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Diffusion Probabilistic Priors for Zero-Shot Low-Dose CT Image Denoising

https://github.com/deezer/musicFPaugment

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Music Augmentation and Denoising For Peak-Based Audio Fingerprinting

https://github.com/deitsp/deitsp

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An Efficient Diffusion-based Non-Autoregressive Solver for Traveling Salesman Problem

https://github.com/demonsjin/blind2unblind

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Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots

https://github.com/deng-ai-lab/sdo

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You Only Look One Step: Accelerating Backpropagation in Diffusion Sampling with Gradient Shortcuts

https://github.com/dengsgithub/composition-learning

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When A Conventional Filter Meets Deep Learning: Basis Composition Learning on Image Filters

https://github.com/dennishein/cpfgmpp_pcct_denoising

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PPFM: Image denoising in photon-counting CT using single-step posterior sampling Poisson flow generative models

https://github.com/deokhk/dotter

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Denoising Table-Text Retrieval for Open-Domain Question Answering

https://github.com/derekchen14/mixture_soft_prompts

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Mixture of Soft Prompts for Controllable Data Generation

https://github.com/desaixie/pa_vdm

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Progressive Autoregressive Video Diffusion Models

https://github.com/devintdha/diffusion-counterfactuals-for-image-regressors

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Diffusion Counterfactuals for Image Regressors

https://github.com/devjake/eeg-diffusion-pytorch

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EEG Synthetic Data Generation Using Probabilistic Diffusion Models

https://github.com/deweihu/oct_ddpm

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Unsupervised Denoising of Retinal OCT with Diffusion Probabilistic Model

https://github.com/dgedon/invertible_kernel_PCA

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Invertible Kernel PCA with Random Fourier Features

https://github.com/dhryougit/learning-to-translate-noise

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Learning to Translate Noise for Robust Image Denoising

https://github.com/dichao-liu/anti-noise_fgvr

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Progressive Multi-task Anti-Noise Learning and Distilling Frameworks for Fine-grained Vehicle Recognition

https://github.com/didriknielsen/argmax_flows

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Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions

https://github.com/diegovalsesia/GPDNet

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Learning Graph-Convolutional Representations for Point Cloud Denoising

https://github.com/diegovalsesia/gcdn

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Image Denoising with Graph-Convolutional Neural Networks

https://github.com/diegovalsesia/mmd-ddm

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Fast Inference in Denoising Diffusion Models via MMD Finetuning

https://github.com/diegovalsesia/speckle2void

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Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks

https://github.com/ding-zj/glode

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Improving Pseudo Labels with Global-Local Denoising Framework for Cross-lingual Named Entity Recognition

https://github.com/dingkeyan93/IQA-optimization

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Comparison of Image Quality Models for Optimization of Image Processing Systems

https://github.com/dinner-group/geom2vec

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Using pretrained graph neural networks with token mixers as geometric featurizers for conformational dynamics

https://github.com/distributionnetworkstudelft/energydiff-pub

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

https://github.com/distrinet/flowpure

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FlowPure: Continuous Normalizing Flows for Adversarial Purification

https://github.com/dit-generalization/dit-generalization.github.io

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On Inductive Biases That Enable Generalization of Diffusion Transformers

https://github.com/ditflow/ditflow

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Video Motion Transfer with Diffusion Transformers

https://github.com/divelab/Noise2Same

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Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising

https://github.com/divnori/rnaflow

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RNAFlow: RNA Structure & Sequence Design via Inverse Folding-Based Flow Matching

https://github.com/divyakraman/blackscholesdiffusion2024

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Prompt Mixing in Diffusion Models using the Black Scholes Algorithm

https://github.com/divyakraman/imposterdiffusion2024

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ImPoster: Text and Frequency Guidance for Subject Driven Action Personalization using Diffusion Models

https://github.com/dlr-mi/atme

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Look ATME: The Discriminator Mean Entropy Needs Attention

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