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 226–250 of 7282 papers

TitleStatusHype
HumanMAC: Masked Motion Completion for Human Motion PredictionCode2
Classifier-guided neural blind deconvolution: a physics-informed denoising module for bearing fault diagnosis under heavy noiseCode2
Hybrid Convolutional and Attention Network for Hyperspectral Image DenoisingCode2
Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask LearningCode2
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial OptimizationCode2
CMGAN: Conformer-Based Metric-GAN for Monaural Speech EnhancementCode2
Collaborative Diffusion for Multi-Modal Face Generation and EditingCode2
DiGress: Discrete Denoising diffusion for graph generationCode2
Improved Immiscible Diffusion: Accelerate Diffusion Training by Reducing Its MiscibilityCode2
A Simple and Model-Free Path Filtering Algorithm for Smoothing and AccuracyCode2
Diffusion Transformer PolicyCode2
Diffusion Recommender ModelCode2
Coherent and Multi-modality Image Inpainting via Latent Space OptimizationCode2
Diffusion-Sharpening: Fine-tuning Diffusion Models with Denoising Trajectory SharpeningCode2
Diffusion Prior-Based Amortized Variational Inference for Noisy Inverse ProblemsCode2
CoMoSpeech: One-Step Speech and Singing Voice Synthesis via Consistency ModelCode2
InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized RationalesCode2
Compressed Image Generation with Denoising Diffusion Codebook ModelsCode2
Compression-Aware One-Step Diffusion Model for JPEG Artifact RemovalCode2
Towards Stabilized and Efficient Diffusion Transformers through Long-Skip-Connections with Spectral ConstraintsCode2
Diffusion Predictive Control with ConstraintsCode2
Conditional Image Synthesis with Diffusion Models: A SurveyCode2
L4DR: LiDAR-4DRadar Fusion for Weather-Robust 3D Object DetectionCode2
Diffusion Probabilistic Models beat GANs on Medical ImagesCode2
DiffusionTrack: Diffusion Model For Multi-Object TrackingCode2
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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