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

Showing 72017225 of 7282 papers

TitleStatusHype
Random Sampling for Diffusion-based Adversarial PurificationCode0
Expressive probabilistic sampling in recurrent neural networksCode0
Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving RegularizationCode0
Scalable Non-Equivariant 3D Molecule Generation via Rotational AlignmentCode0
Informed Graph Learning By Domain Knowledge Injection and Smooth Graph Signal RepresentationCode0
Mixed Graph Signal Analysis of Joint Image Denoising / InterpolationCode0
Towards Robust Toxic Content ClassificationCode0
Composite Reward Design in PPO-Driven Adaptive FilteringCode0
Comprehensive Generative Replay for Task-Incremental Segmentation with Concurrent Appearance and Semantic ForgettingCode0
CAT Pruning: Cluster-Aware Token Pruning For Text-to-Image Diffusion ModelsCode0
Approximate Bayesian Computation with the Sliced-Wasserstein DistanceCode0
Deep End-to-end Fingerprint Denoising and InpaintingCode0
You Can't Ignore Either: Unifying Structure and Feature Denoising for Robust Graph LearningCode0
Scaling Laws For Deep Learning Based Image ReconstructionCode0
Compressed Sensing: A Discrete Optimization ApproachCode0
Mixture of Soft Prompts for Controllable Data GenerationCode0
Sliced Wasserstein with Random-Path Projecting DirectionsCode0
EyeBench: A Call for More Rigorous Evaluation of Retinal Image EnhancementCode0
Data-Aware Training Quality Monitoring and Certification for Reliable Deep LearningCode0
A Generative Adversarial Approach To ECG Synthesis And DenoisingCode0
F2FLDM: Latent Diffusion Models with Histopathology Pre-Trained Embeddings for Unpaired Frozen Section to FFPE TranslationCode0
ρ-Diffusion: A diffusion-based density estimation framework for computational physicsCode0
Deep learning Framework for Mobile MicroscopyCode0
Face De-Spoofing: Anti-Spoofing via Noise ModelingCode0
Face Manifold: Manifold Learning for Synthetic Face GenerationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81Unverified
2Pixel-shuffling DownsamplingPSNR38.4Unverified
3TWSCPSNR37.93Unverified
4CBDNet(Syn)PSNR37.57Unverified
5MCWNNMPSNR37.38Unverified
6Han et alPSNR35.95Unverified
7FFDNetPSNR34.4Unverified
8TNRDPSNR33.65Unverified
9CDnCNN-BPSNR32.43Unverified
10NLRNPSNR30.8Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61Unverified