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 4301–4325 of 7282 papers

TitleStatusHype
Continuous longitudinal fetus brain atlas construction via implicit neural representation—0
Spline-Like Wavelet Filterbanks with Perfect Reconstruction on Arbitrary Graphs—0
Noise2SR: Learning to Denoise from Super-Resolved Single Noisy Fluorescence Image—0
vec2text with Round-Trip Translations—0
Few Clean Instances Help Denoising Distant SupervisionCode0
Considering Image Information and Self-similarity: A Compositional Denoising NetworkCode0
DEANet: Decomposition Enhancement and Adjustment Network for Low-Light Image Enhancement—0
Robust Product Classification with Instance-Dependent Noise—0
PET image denoising based on denoising diffusion probabilistic models—0
Blurring Diffusion Models—0
Manifold Rewiring for Unlabeled Imaging—0
Soft Diffusion: Score Matching for General Corruptions—0
Diffusion Models in Vision: A SurveyCode2
Learning to Generate Realistic LiDAR Point CloudsCode1
G2L: A Global to Local Alignment Method for Unsupervised Domain Adaptive Semantic Segmentation—0
Spach Transformer: Spatial and Channel-wise Transformer Based on Local and Global Self-attentions for PET Image DenoisingCode1
Video Restoration with a Deep Plug-and-Play Prior—0
LRT: An Efficient Low-Light Restoration Transformer for Dark Light Field Images—0
Learning to Predict on Octree for Scalable Point Cloud Geometry Coding—0
A Multi-scale Video Denoising Algorithm for Raw Image—0
Large Graph Signal Denoising with Application to Differential PrivacyCode0
Geometric and Learning-based Mesh Denoising: A Comprehensive Survey—0
PCDNF: Revisiting Learning-based Point Cloud Denoising via Joint Normal Filtering—0
Practical Operator Sketching Framework for Accelerating Iterative Data-Driven Solutions in Inverse Problems—0
ELMformer: Efficient Raw Image Restoration with a Locally Multiplicative TransformerCode0
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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