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 826–850 of 7282 papers

TitleStatusHype
PrimDiffusion: Volumetric Primitives Diffusion for 3D Human GenerationCode1
Training Neural Networks on RAW and HDR Images for Restoration TasksCode1
TokenCompose: Text-to-Image Diffusion with Token-level SupervisionCode1
Machine Vision Therapy: Multimodal Large Language Models Can Enhance Visual Robustness via Denoising In-Context LearningCode1
Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object DetectionCode1
Fully Spiking Denoising Diffusion Implicit ModelsCode1
EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion GenerationCode1
Unsupervised Anomaly Detection using Aggregated Normative DiffusionCode1
A Conditional Denoising Diffusion Probabilistic Model for Point Cloud UpsamplingCode1
Planning as In-Painting: A Diffusion-Based Embodied Task Planning Framework for Environments under UncertaintyCode1
SynFundus-1M: A High-quality Million-scale Synthetic fundus images Dataset with Fifteen Types of AnnotationCode1
CAT-DM: Controllable Accelerated Virtual Try-on with Diffusion ModelCode1
Contrastive Denoising Score for Text-guided Latent Diffusion Image EditingCode1
MagDiff: Multi-Alignment Diffusion for High-Fidelity Video Generation and EditingCode1
Unsupervised Keypoints from Pretrained Diffusion ModelsCode1
SODA: Bottleneck Diffusion Models for Representation LearningCode1
D4AM: A General Denoising Framework for Downstream Acoustic ModelsCode1
ReMoS: 3D Motion-Conditioned Reaction Synthesis for Two-Person InteractionsCode1
DTP-Net: Learning to Reconstruct EEG signals in Time-Frequency Domain by Multi-scale Feature ReuseCode1
LFSRDiff: Light Field Image Super-Resolution via Diffusion ModelsCode1
Ultra-short-term multi-step wind speed prediction for wind farms based on adaptive noise reduction technology and temporal convolutional networkCode1
TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion ModelsCode1
Resfusion: Denoising Diffusion Probabilistic Models for Image Restoration Based on Prior Residual NoiseCode1
Continual Learning of Diffusion Models with Generative DistillationCode1
MetaCloak: Preventing Unauthorized Subject-driven Text-to-image Diffusion-based Synthesis via Meta-learningCode1
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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