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 1401–1450 of 7282 papers

TitleStatusHype
Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEGCode1
LatentEditor: Text Driven Local Editing of 3D ScenesCode1
Differentiable Manifold Reconstruction for Point Cloud DenoisingCode1
Learnability Enhancement for Low-light Raw Denoising: Where Paired Real Data Meets Noise ModelingCode1
Assessment of Data Consistency through Cascades of Independently Recurrent Inference Machines for fast and robust accelerated MRI reconstructionCode1
Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot ClassificationCode1
DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic ModelsCode1
Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance ScaleCode1
Learning multi-scale local conditional probability models of imagesCode1
Learning Robust Recommender from Noisy Implicit FeedbackCode1
Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise MappingCode1
DiffDA: a Diffusion Model for Weather-scale Data AssimilationCode1
DiffFashion: Reference-based Fashion Design with Structure-aware Transfer by Diffusion ModelsCode1
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform GenerationCode1
DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein TracesCode1
Learning to Generate Realistic LiDAR Point CloudsCode1
Learning to See in the DarkCode1
DAEMA: Denoising Autoencoder with Mask AttentionCode1
Crystal Structure Prediction by Joint Equivariant DiffusionCode1
Legacy Photo Editing with Learned Noise PriorCode1
Less is More: Reweighting Important Spectral Graph Features for RecommendationCode1
CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy LabelsCode1
DiffCharge: Generating EV Charging Scenarios via a Denoising Diffusion ModelCode1
CTformer: Convolution-free Token2Token Dilated Vision Transformer for Low-dose CT DenoisingCode1
DiffPortrait3D: Controllable Diffusion for Zero-Shot Portrait View SynthesisCode1
Devil is in the Uniformity: Exploring Diverse Learners within Transformer for Image RestorationCode1
CT-Mamba: A Hybrid Convolutional State Space Model for Low-Dose CT DenoisingCode1
LIPT: Latency-aware Image Processing TransformerCode1
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
LIR: A Lightweight Baseline for Image RestorationCode1
DFormer: Diffusion-guided Transformer for Universal Image SegmentationCode1
Curriculum Disentangled Recommendation with Noisy Multi-feedbackCode1
DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly DetectionCode1
Exploring the Loss Landscape in Neural Architecture SearchCode1
D4AM: A General Denoising Framework for Downstream Acoustic ModelsCode1
DETA: Denoised Task Adaptation for Few-Shot LearningCode1
Customizing 360-Degree Panoramas through Text-to-Image Diffusion ModelsCode1
CutDiffusion: A Simple, Fast, Cheap, and Strong Diffusion Extrapolation MethodCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from ImageCode1
M2DF: Multi-grained Multi-curriculum Denoising Framework for Multimodal Aspect-based Sentiment AnalysisCode1
M4Raw: A multi-contrast, multi-repetition, multi-channel MRI k-space dataset for low-field MRI researchCode1
DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion DelineationCode1
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game EncodingCode1
A Cheaper and Better Diffusion Language Model with Soft-Masked NoiseCode1
MagicMix: Semantic Mixing with Diffusion ModelsCode1
D4Explainer: In-Distribution GNN Explanations via Discrete Denoising DiffusionCode1
CycleISP: Real Image Restoration via Improved Data SynthesisCode1
Designing and Training of A Dual CNN for Image DenoisingCode1
Denoising Task Routing for Diffusion ModelsCode1
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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