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 2601–2625 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
TIGER: Time-Varying Denoising Model for 3D Point Cloud Generation with Diffusion ProcessCode1
Denoising Point Clouds in Latent Space via Graph Convolution and Invertible Neural NetworkCode1
IPoD: Implicit Field Learning with Point Diffusion for Generalizable 3D Object Reconstruction from Single RGB-D Images—0
ScoreHypo: Probabilistic Human Mesh Estimation with Hypothesis Scoring—0
Multiway Point Cloud Mosaicking with Diffusion and Global OptimizationCode1
Taming Stable Diffusion for Text to 360 Panorama Image Generation—0
ZERO-IG: Zero-Shot Illumination-Guided Joint Denoising and Adaptive Enhancement for Low-Light ImagesCode2
TexOct: Generating Textures of 3D Models with Octree-based Diffusion—0
Unmixing Diffusion for Self-Supervised Hyperspectral Image Denoising—0
FlowDiffuser: Advancing Optical Flow Estimation with Diffusion ModelsCode2
Distraction is All You Need: Memory-Efficient Image Immunization against Diffusion-Based Image Editing—0
Patch2Self2: Self-supervised Denoising on Coresets via Matrix Sketching—0
Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous and Instruction-guided Driving—0
Slice3D: Multi-Slice Occlusion-Revealing Single View 3D Reconstruction—0
DiffForensics: Leveraging Diffusion Prior to Image Forgery Detection and Localization—0
Robust Image Denoising through Adversarial Frequency MixupCode1
GPLD3D: Latent Diffusion of 3D Shape Generative Models by Enforcing Geometric and Physical Priors—0
DeIL: Direct-and-Inverse CLIP for Open-World Few-Shot LearningCode1
HOIAnimator: Generating Text-prompt Human-object Animations using Novel Perceptive Diffusion Models—0
Towards More Accurate Diffusion Model Acceleration with A Timestep TunerCode0
Real-World Mobile Image Denoising Dataset with Efficient BaselinesCode2
Show:102550
← PrevPage 105 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