SOTAVerified

Denoising

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.

( Image credit: Beyond a Gaussian Denoiser )

Papers

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Showing 3501–3525 of 7282 papers

TitleStatusHype
UDPM: Upsampling Diffusion Probabilistic ModelsCode1
Zero-shot Generation of Training Data with Denoising Diffusion Probabilistic Model for Handwritten Chinese Character Recognition—0
Efficient Neural Music Generation—0
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)Code1
Weakly-Supervised Speech Pre-training: A Case Study on Target Speech Recognition—0
Anomaly Detection with Conditioned Denoising Diffusion ModelsCode2
Diffusion Probabilistic Priors for Zero-Shot Low-Dose CT Image DenoisingCode1
Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time StepsCode1
A Neural Space-Time Representation for Text-to-Image PersonalizationCode1
Denoising Bottleneck with Mutual Information Maximization for Video Multimodal FusionCode0
Textless Speech-to-Speech Translation With Limited Parallel DataCode0
SAIL: Search-Augmented Instruction Learning—0
From Shortcuts to Triggers: Backdoor Defense with Denoised PoECode0
Least Squares Regression Can Exhibit Under-Parameterized Double Descent—0
CoLaDa: A Collaborative Label Denoising Framework for Cross-lingual Named Entity RecognitionCode2
Sin3DM: Learning a Diffusion Model from a Single 3D Textured ShapeCode1
PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptions—0
DiffHand: End-to-End Hand Mesh Reconstruction via Diffusion Models—0
Realistic Noise Synthesis with Diffusion ModelsCode0
WaveDM: Wavelet-Based Diffusion Models for Image RestorationCode1
When Does Monolingual Data Help Multilingual Translation: The Role of Domain and Model Scale—0
Basis Pursuit Denoising via Recurrent Neural Network Applied to Super-resolving SAR Tomography—0
MOTRv3: Release-Fetch Supervision for End-to-End Multi-Object Tracking—0
Masked Modeling Duo for Speech: Specializing General-Purpose Audio Representation to Speech using Denoising Distillation—0
Multi-Echo Denoising in Adverse WeatherCode1
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All datasetsDarmstadt Noise DatasetDIV2KDNDiris

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81—Unverified
2Pixel-shuffling DownsamplingPSNR38.4—Unverified
3TWSCPSNR37.93—Unverified
4CBDNet(Syn)PSNR37.57—Unverified
5MCWNNMPSNR37.38—Unverified
6Han et alPSNR35.95—Unverified
7FFDNetPSNR34.4—Unverified
8TNRDPSNR33.65—Unverified
9CDnCNN-BPSNR32.43—Unverified
10NLRNPSNR30.8—Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92—Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64—Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61—Unverified