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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 601–625 of 7282 papers

TitleStatusHype
Diff-Reg v1: Diffusion Matching Model for Registration ProblemCode1
Adaptive Consistency Prior Based Deep Network for Image DenoisingCode1
DiffSDS: A language diffusion model for protein backbone inpainting under geometric conditions and constraintsCode1
DiffSim: Taming Diffusion Models for Evaluating Visual SimilarityCode1
DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic ModelCode1
DiffPortrait3D: Controllable Diffusion for Zero-Shot Portrait View SynthesisCode1
AKDT: Adaptive Kernel Dilation Transformer for Effective Image DenoisingCode1
DiffProsody: Diffusion-based Latent Prosody Generation for Expressive Speech Synthesis with Prosody Conditional Adversarial TrainingCode1
DiffPLF: A Conditional Diffusion Model for Probabilistic Forecasting of EV Charging LoadCode1
DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain PackingCode1
DiffPO: A causal diffusion model for learning distributions of potential outcomesCode1
DiffQRCoder: Diffusion-based Aesthetic QR Code Generation with Scanning Robustness Guided Iterative RefinementCode1
Diffusion Model for Dense MatchingCode1
Empowering Diffusion Models on the Embedding Space for Text GenerationCode1
A Bregman Learning Framework for Sparse Neural NetworksCode1
DiffO: Single-step Diffusion for Image Compression at Ultra-Low BitratesCode1
Diffusion Deformable Model for 4D Temporal Medical Image GenerationCode1
Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure TimesCode1
Enhancing Robustness Against Adversarial Examples in Network Intrusion Detection SystemsCode1
AIM 2020 Challenge on Learned Image Signal Processing PipelineCode1
2D medical image synthesis using transformer-based denoising diffusion probabilistic modelCode1
Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEGCode1
DiffDA: a Diffusion Model for Weather-scale Data AssimilationCode1
Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-ExpertsCode1
Differentiable Manifold Reconstruction for Point Cloud DenoisingCode1
Show:102550
← PrevPage 25 of 292Next →
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