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 701–750 of 7282 papers

TitleStatusHype
A Simple and Robust Correlation Filtering Method for Text-based Person SearchCode1
Assessment of Data Consistency through Cascades of Independently Recurrent Inference Machines for fast and robust accelerated MRI reconstructionCode1
Diffusion Model for Dense MatchingCode1
Diffusion-based Pose Refinement and Muti-hypothesis Generation for 3D Human Pose EstimaitonCode1
DiffFashion: Reference-based Fashion Design with Structure-aware Transfer by Diffusion ModelsCode1
Diff-IP2D: Diffusion-Based Hand-Object Interaction Prediction on Egocentric VideosCode1
Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEGCode1
Action-Conditioned 3D Human Motion Synthesis with Transformer VAECode1
Differentiable Manifold Reconstruction for Point Cloud DenoisingCode1
DifFIQA: Face Image Quality Assessment Using Denoising Diffusion Probabilistic ModelsCode1
Empowering Diffusion Models on the Embedding Space for Text GenerationCode1
DiffCharge: Generating EV Charging Scenarios via a Denoising Diffusion ModelCode1
Diffusion Model Based Posterior Sampling for Noisy Linear Inverse ProblemsCode1
Diffusion Model Based Visual Compensation Guidance and Visual Difference Analysis for No-Reference Image Quality AssessmentCode1
DiffCMR: Fast Cardiac MRI Reconstruction with Diffusion Probabilistic ModelsCode1
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform GenerationCode1
DiffDA: a Diffusion Model for Weather-scale Data AssimilationCode1
Diffusion Models Beat GANs on Image ClassificationCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
DialogLM: Pre-trained Model for Long Dialogue Understanding and SummarizationCode1
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from DataCode1
DFormer: Diffusion-guided Transformer for Universal Image SegmentationCode1
A generic diffusion-based approach for 3D human pose prediction in the wildCode1
Diffusion Models Learn Low-Dimensional Distributions via Subspace ClusteringCode1
DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein TracesCode1
Diffusion Policies creating a Trust Region for Offline Reinforcement LearningCode1
DiffO: Single-step Diffusion for Image Compression at Ultra-Low BitratesCode1
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game EncodingCode1
DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion DelineationCode1
Diffusion Priors for Variational Likelihood Estimation and Image DenoisingCode1
Designing and Training of A Dual CNN for Image DenoisingCode1
DenoSent: A Denoising Objective for Self-Supervised Sentence Representation LearningCode1
DenoMamba: A fused state-space model for low-dose CT denoisingCode1
Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object DetectionCode1
DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly DetectionCode1
Denoising Relation Extraction from Document-level Distant SupervisionCode1
Diffusive Gibbs SamplingCode1
DIFFVSGG: Diffusion-Driven Online Video Scene Graph GenerationCode1
Denoising Point Clouds in Latent Space via Graph Convolution and Invertible Neural NetworkCode1
Denoising Task Routing for Diffusion ModelsCode1
4D Facial Expression Diffusion ModelCode1
Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure TimesCode1
A Variational Perspective on Solving Inverse Problems with Diffusion ModelsCode1
Discovering Interpretable Directions in the Semantic Latent Space of Diffusion ModelsCode1
ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT DenoisingCode1
Denoising of 3D MR images using a voxel-wise hybrid residual MLP-CNN model to improve small lesion diagnostic confidenceCode1
DETA: Denoised Task Adaptation for Few-Shot LearningCode1
Denoising Masked AutoEncoders Help Robust ClassificationCode1
Denoising Lévy Probabilistic ModelsCode1
Denoising MCMC for Accelerating Diffusion-Based Generative 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