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 701–725 of 7282 papers

TitleStatusHype
Simultaneous Tri-Modal Medical Image Fusion and Super-Resolution using Conditional Diffusion ModelCode1
Denoising: from classical methods to deep CNNsCode1
A Comprehensive Survey for Hyperspectral Image Classification: The Evolution from Conventional to Transformers and Mamba ModelsCode1
CutDiffusion: A Simple, Fast, Cheap, and Strong Diffusion Extrapolation MethodCode1
Collaborative Filtering Based on Diffusion Models: Unveiling the Potential of High-Order ConnectivityCode1
SSDiff: Spatial-spectral Integrated Diffusion Model for Remote Sensing PansharpeningCode1
Molecular relaxation by reverse diffusion with time step predictionCode1
Digging into contrastive learning for robust depth estimation with diffusion modelsCode1
WiTUnet: A U-Shaped Architecture Integrating CNN and Transformer for Improved Feature Alignment and Local Information FusionCode1
RoofDiffusion: Constructing Roofs from Severely Corrupted Point Data via DiffusionCode1
NIR-Assisted Image Denoising: A Selective Fusion Approach and A Real-World Benchmark DatasetCode1
scRDiT: Generating single-cell RNA-seq data by diffusion transformers and accelerating samplingCode1
LIPT: Latency-aware Image Processing TransformerCode1
Rethinking the Spatial Inconsistency in Classifier-Free Diffusion GuidanceCode1
Taming Transformers for Realistic Lidar Point Cloud GenerationCode1
Dual-Scale Transformer for Large-Scale Single-Pixel ImagingCode1
Latent-based Diffusion Model for Long-tailed RecognitionCode1
Real-time Noise Source Estimation of a Camera System from an Image and MetadataCode1
OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning DenoisingCode1
WcDT: World-centric Diffusion Transformer for Traffic Scene GenerationCode1
DPMesh: Exploiting Diffusion Prior for Occluded Human Mesh RecoveryCode1
DeeDSR: Towards Real-World Image Super-Resolution via Degradation-Aware Stable DiffusionCode1
Modeling State Shifting via Local-Global Distillation for Event-Frame Gaze TrackingCode1
Diff-Reg v1: Diffusion Matching Model for Registration ProblemCode1
Binarized Low-light Raw Video EnhancementCode1
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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