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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3226–3250 of 7282 papers

TitleStatusHype
DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion DelineationCode1
Generative Approach for Probabilistic Human Mesh Recovery using Diffusion ModelsCode1
Sketch and Text Guided Diffusion Model for Colored Point Cloud Generation—0
Transformer-Based Denoising of Mechanical Vibration Signals—0
Rethinking Class Activation Maps for Segmentation: Revealing Semantic Information in Shallow Layers by Reducing Noise—0
SDDM: Score-Decomposed Diffusion Models on Manifolds for Unpaired Image-to-Image Translation—0
DiffGANPaint: Fast Inpainting Using Denoising Diffusion GANs—0
Synthesising Rare Cataract Surgery Samples with Guided Diffusion ModelsCode0
Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models—0
Adversarial Training of Denoising Diffusion Model Using Dual Discriminators for High-Fidelity Multi-Speaker TTS—0
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain ImagesCode1
Leveraging Side Information for Ligand Conformation Generation using Diffusion-Based Approaches—0
EmbeddingTree: Hierarchical Exploration of Entity Features in Embedding—0
Contrast-augmented Diffusion Model with Fine-grained Sequence Alignment for Markup-to-Image GenerationCode0
Patched Denoising Diffusion Models For High-Resolution Image SynthesisCode1
Can We Transfer Noise Patterns? A Multi-environment Spectrum Analysis Model Using Generated CasesCode0
EC-Conf: An Ultra-fast Diffusion Model for Molecular Conformation Generation with Equivariant ConsistencyCode1
Decomposition Ascribed Synergistic Learning for Unified Image Restoration—0
PressureTransferNet: Human Attribute Guided Dynamic Ground Pressure Profile Transfer using 3D simulated Pressure Maps—0
Toward Zero-shot Character Recognition: A Gold Standard Dataset with Radical-level Annotations—0
Domain Adaptation based on Human Feedback for Enhancing Generative Model Denoising Abilities—0
Diffusion Model for Camouflaged Object DetectionCode0
Unleashing the Power of Self-Supervised Image Denoising: A Comprehensive Review—0
MetaDiff: Meta-Learning with Conditional Diffusion for Few-Shot Learning—0
Don't be so negative! Score-based Generative Modeling with Oracle-assisted Guidance—0
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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