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 151175 of 7282 papers

TitleStatusHype
Drag Your Noise: Interactive Point-based Editing via Diffusion Semantic PropagationCode2
All-In-One Medical Image Restoration via Task-Adaptive RoutingCode2
Beyond Text: Frozen Large Language Models in Visual Signal ComprehensionCode2
DPoser: Diffusion Model as Robust 3D Human Pose PriorCode2
Dreamer XL: Towards High-Resolution Text-to-3D Generation via Trajectory Score MatchingCode2
EAMamba: Efficient All-Around Vision State Space Model for Image RestorationCode2
Aligning Text-to-Image Diffusion Models with Reward BackpropagationCode2
Dita: Scaling Diffusion Transformer for Generalist Vision-Language-Action PolicyCode2
BAMM: Bidirectional Autoregressive Motion ModelCode2
dKV-Cache: The Cache for Diffusion Language ModelsCode2
DnLUT: Ultra-Efficient Color Image Denoising via Channel-Aware Lookup TablesCode2
DiSA: Diffusion Step Annealing in Autoregressive Image GenerationCode2
Discrete Diffusion Modeling by Estimating the Ratios of the Data DistributionCode2
DiGress: Discrete Denoising diffusion for graph generationCode2
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial OptimizationCode2
DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape GenerationCode2
DocDiff: Document Enhancement via Residual Diffusion ModelsCode2
EasyText: Controllable Diffusion Transformer for Multilingual Text RenderingCode2
Flow-Guided Diffusion for Video InpaintingCode2
Diffusion Probabilistic Models beat GANs on Medical ImagesCode2
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse ProblemsCode2
Diffusion Recommender ModelCode2
Diffusion Models in Vision: A SurveyCode2
Diffusion Predictive Control with ConstraintsCode2
Diffusion-Sharpening: Fine-tuning Diffusion Models with Denoising Trajectory SharpeningCode2
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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