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 2601–2650 of 7282 papers

TitleStatusHype
GeoPos: A Minimal Positional Encoding for Enhanced Fine-Grained Details in Image Synthesis Using Convolutional Neural Networks—0
Robust single-particle cryo-EM image denoising and restoration—0
DiffLoc: Diffusion Model for Outdoor LiDAR LocalizationCode2
DiffHuman: Probabilistic Photorealistic 3D Reconstruction of Humans—0
ScoreHypo: Probabilistic Human Mesh Estimation with Hypothesis Scoring—0
Multiway Point Cloud Mosaicking with Diffusion and Global OptimizationCode1
Denoising Point Clouds in Latent Space via Graph Convolution and Invertible Neural NetworkCode1
TexOct: Generating Textures of 3D Models with Octree-based Diffusion—0
ZERO-IG: Zero-Shot Illumination-Guided Joint Denoising and Adaptive Enhancement for Low-Light ImagesCode2
IPoD: Implicit Field Learning with Point Diffusion for Generalizable 3D Object Reconstruction from Single RGB-D Images—0
FlowDiffuser: Advancing Optical Flow Estimation with Diffusion ModelsCode2
Unmixing Diffusion for Self-Supervised Hyperspectral Image Denoising—0
Slice3D: Multi-Slice Occlusion-Revealing Single View 3D Reconstruction—0
Patch2Self2: Self-supervised Denoising on Coresets via Matrix Sketching—0
Distraction is All You Need: Memory-Efficient Image Immunization against Diffusion-Based Image Editing—0
Taming Stable Diffusion for Text to 360 Panorama Image Generation—0
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous and Instruction-guided Driving—0
TIGER: Time-Varying Denoising Model for 3D Point Cloud Generation with Diffusion ProcessCode1
DiffForensics: Leveraging Diffusion Prior to Image Forgery Detection and Localization—0
DeIL: Direct-and-Inverse CLIP for Open-World Few-Shot LearningCode1
Hyper-MD: Mesh Denoising with Customized Parameters Aware of Noise Intensity and Geometric Characteristics—0
GPLD3D: Latent Diffusion of 3D Shape Generative Models by Enforcing Geometric and Physical Priors—0
Inversion-Free Image Editing with Language-Guided Diffusion ModelsCode3
Z*: Zero-shot Style Transfer via Attention ReweightingCode2
HOIAnimator: Generating Text-prompt Human-object Animations using Novel Perceptive Diffusion Models—0
Robust Image Denoising through Adversarial Frequency MixupCode1
Dual Prior Unfolding for Snapshot Compressive ImagingCode1
CoDe: An Explicit Content Decoupling Framework for Image Restoration—0
DiffusionTrack: Point Set Diffusion Model for Visual Object TrackingCode0
Real-World Mobile Image Denoising Dataset with Efficient BaselinesCode2
Towards More Accurate Diffusion Model Acceleration with A Timestep TunerCode0
Exposure Bracketing Is All You Need For A High-Quality ImageCode2
Revisiting Nonlocal Self-Similarity from Continuous Representation—0
Depth Map Denoising Network and Lightweight Fusion Network for Enhanced 3D Face Recognition—0
Hyperspectral Image Denoising via Spatial-Spectral Recurrent TransformerCode0
UGPNet: Universal Generative Prior for Image Restoration—0
SAFE-SIM: Safety-Critical Closed-Loop Traffic Simulation with Diffusion-Controllable Adversaries—0
Diff-PCR: Diffusion-Based Correspondence Searching in Doubly Stochastic Matrix Space for Point Cloud Registration—0
Diffusion Model with Perceptual Loss—0
Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion ModelsCode1
6D-Diff: A Keypoint Diffusion Framework for 6D Object Pose Estimation—0
Improving Image Restoration through Removing Degradations in Textual RepresentationsCode1
Learning the Dynamic Correlations and Mitigating Noise by Hierarchical Convolution for Long-term Sequence ForecastingCode0
Grounding-Prompter: Prompting LLM with Multimodal Information for Temporal Sentence Grounding in Long Videos—0
Restoration by Generation with Constrained Priors—0
Natural Adversarial Patch Generation Method Based on Latent Diffusion Model—0
Self-supervised Pretraining for Robust Personalized Voice Activity Detection in Adverse Conditions—0
Image Restoration by Denoising Diffusion Models with Iteratively Preconditioned GuidanceCode1
Learn From Orientation Prior for Radiograph Super-Resolution: Orientation Operator Transformer—0
PanGu-Draw: Advancing Resource-Efficient Text-to-Image Synthesis with Time-Decoupled Training and Reusable Coop-Diffusion—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