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 901–925 of 7282 papers

TitleStatusHype
BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image RestorationCode1
Diffusion Models for Constrained DomainsCode1
fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functionsCode1
Bilevel Fast Scene Adaptation for Low-Light Image EnhancementCode1
3D Vessel Graph Generation Using Denoising DiffusionCode1
FlexDiT: Dynamic Token Density Control for Diffusion TransformerCode1
Diffusion Models Learn Low-Dimensional Distributions via Subspace ClusteringCode1
Binarized Low-light Raw Video EnhancementCode1
IterativePFN: True Iterative Point Cloud FilteringCode1
Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly DetectionCode1
FLIGHT Mode On: A Feather-Light Network for Low-Light Image EnhancementCode1
Diffusion Posterior Illumination for Ambiguity-aware Inverse RenderingCode1
Convolutional Proximal Neural Networks and Plug-and-Play AlgorithmsCode1
Adversarial purification with Score-based generative modelsCode1
Accelerating Diffusion Models via Early Stop of the Diffusion ProcessCode1
BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder ArchitectureCode1
CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and GeneralizationCode1
bit2bit: 1-bit quanta video reconstruction via self-supervised photon predictionCode1
A Continuous Time Framework for Discrete Denoising ModelsCode1
Joint HDR Denoising and Fusion: A Real-World Mobile HDR Image DatasetCode1
CoT-BERT: Enhancing Unsupervised Sentence Representation through Chain-of-ThoughtCode1
Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object DetectionCode1
Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image AttenuationCode1
Blind2Unblind: Self-Supervised Image Denoising with Visible Blind SpotsCode1
FLIP: A Difference Evaluator for Alternating ImagesCode1
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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