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 3701–3725 of 7282 papers

TitleStatusHype
MirrorDiffusion: Stabilizing Diffusion Process in Zero-shot Image Translation by Prompts Redescription and Beyond—0
Tailoring Frictional Properties of Surfaces Using Diffusion Models—0
Two-stage Progressive Residual Dense Attention Network for Image DenoisingCode0
Geometric-Facilitated Denoising Diffusion Model for 3D Molecule GenerationCode0
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational PosteriorsCode0
Bring Metric Functions into Diffusion Models—0
Improving Diffusion-Based Image Synthesis with Context Prediction—0
DDPM based X-ray Image Synthesizer—0
GeoPos: A Minimal Positional Encoding for Enhanced Fine-Grained Details in Image Synthesis Using Convolutional Neural Networks—0
DiffYOLO: Object Detection for Anti-Noise via YOLO and Diffusion Models—0
Robust single-particle cryo-EM image denoising and restoration—0
Towards More Accurate Diffusion Model Acceleration with A Timestep TunerCode0
DiffusionTrack: Point Set Diffusion Model for Visual Object TrackingCode0
DiffHuman: Probabilistic Photorealistic 3D Reconstruction of Humans—0
GPLD3D: Latent Diffusion of 3D Shape Generative Models by Enforcing Geometric and Physical Priors—0
TexOct: Generating Textures of 3D Models with Octree-based Diffusion—0
Taming Stable Diffusion for Text to 360 Panorama Image Generation—0
CoDe: An Explicit Content Decoupling Framework for Image Restoration—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
HOIAnimator: Generating Text-prompt Human-object Animations using Novel Perceptive Diffusion Models—0
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous and Instruction-guided Driving—0
Revisiting Nonlocal Self-Similarity from Continuous Representation—0
ScoreHypo: Probabilistic Human Mesh Estimation with Hypothesis Scoring—0
IPoD: Implicit Field Learning with Point Diffusion for Generalizable 3D Object Reconstruction from Single RGB-D Images—0
Show:102550
← PrevPage 149 of 292Next →
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