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 2151–2175 of 7282 papers

TitleStatusHype
Towards Robust Time-of-Flight Depth Denoising with Confidence-Aware Diffusion Model—0
PCM : Picard Consistency Model for Fast Parallel Sampling of Diffusion Models—0
Unified Uncertainty-Aware Diffusion for Multi-Agent Trajectory Modeling—0
Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos—0
Dig2DIG: Dig into Diffusion Information Gains for Image Fusion—0
Hiding Images in Diffusion Models by Editing Learned Score FunctionsCode0
Training-free Diffusion Acceleration with Bottleneck Sampling—0
AIM2PC: Aerial Image to 3D Building Point Cloud ReconstructionCode0
Universal Architectures for the Learning of Polyhedral Norms and Convex Regularizers—0
HunyuanPortrait: Implicit Condition Control for Enhanced Portrait Animation—0
Video-T1: Test-Time Scaling for Video Generation—0
Discriminative protein sequence modelling with Latent Space Diffusion—0
Unified Geometry and Color Compression Framework for Point Clouds via Generative Diffusion Priors—0
SNRAware: Improved Deep Learning MRI Denoising with SNR Unit Training and G-factor Map Augmentation—0
Efficient Diffusion Training through Parallelization with Truncated Karhunen-Loève Expansion—0
Aligning Foundation Model Priors and Diffusion-Based Hand Interactions for Occlusion-Resistant Two-Hand Reconstruction—0
Guidance Free Image Editing via Explicit Conditioning—0
Accelerated Cardiac Parametric Mapping using Deep Learning-Refined Subspace ModelsCode0
Fractal-IR: A Unified Framework for Efficient and Scalable Image Restoration—0
Towards Transformer-Based Aligned Generation with Self-Coherence Guidance—0
A-IDE : Agent-Integrated Denoising Experts—0
Generating, Fast and Slow: Scalable Parallel Video Generation with Video Interface Networks—0
Exploring the Efficacy of Partial Denoising Using Bit Plane Slicing for Enhanced Fracture Identification: A Comparative Study of Deep Learning-Based Approaches and Handcrafted Feature Extraction Techniques—0
Recovering Pulse Waves from Video Using Deep Unrolling and Deep Equilibrium Models—0
BlockDance: Reuse Structurally Similar Spatio-Temporal Features to Accelerate Diffusion Transformers—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