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 176–200 of 7282 papers

TitleStatusHype
DiGress: Discrete Denoising diffusion for graph generationCode2
DiSA: Diffusion Step Annealing in Autoregressive Image GenerationCode2
DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape GenerationCode2
Diffusion Transformer PolicyCode2
AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq ModelCode2
Diffusion-Sharpening: Fine-tuning Diffusion Models with Denoising Trajectory SharpeningCode2
Aligning Text-to-Image Diffusion Models with Reward BackpropagationCode2
All-In-One Medical Image Restoration via Task-Adaptive RoutingCode2
DiffusionTrack: Diffusion Model For Multi-Object TrackingCode2
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial OptimizationCode2
Be Yourself: Bounded Attention for Multi-Subject Text-to-Image GenerationCode2
DocDiff: Document Enhancement via Residual Diffusion ModelsCode2
DPoser: Diffusion Model as Robust 3D Human Pose PriorCode2
Dita: Scaling Diffusion Transformer for Generalist Vision-Language-Action PolicyCode2
Dreamer XL: Towards High-Resolution Text-to-3D Generation via Trajectory Score MatchingCode2
DualDn: Dual-domain Denoising via Differentiable ISPCode2
A Geometric Perspective on Diffusion ModelsCode2
DynamiCtrl: Rethinking the Basic Structure and the Role of Text for High-quality Human Image AnimationCode2
EAMamba: Efficient All-Around Vision State Space Model for Image RestorationCode2
Diffusion Predictive Control with ConstraintsCode2
Blue noise for diffusion modelsCode2
EDICT: Exact Diffusion Inversion via Coupled TransformationsCode2
Effective Cloud Removal for Remote Sensing Images by an Improved Mean-Reverting Denoising Model with Elucidated Design SpaceCode2
An Edit Friendly DDPM Noise Space: Inversion and ManipulationsCode2
Spatio-Temporal Few-Shot Learning via Diffusive Neural Network GenerationCode2
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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